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Job Title: Cloud Data Platform Engineer About the Job you are considering: As the Cloud Data Platform Engineer you will be key member in a cross-functional team developing products, API’s and pipelines for enabling a modern and well-equipped Data Engineering landscape for our customers, where security, governance and controls are at the forefront for rapid data product development. You will be responsible for the development of distributed systems, infrastructure and API’s/Pipelines to ensure that our data engineering platforms are performant, scalable and robust. Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; Your Role: • Build and maintain data models using DBT, • Write complex SQL transformations to clean and structure data, • Develop modular, reusable data pipelines, • Implement data testing and validation (e.g., schema tests, data quality checks), • Manage data documentation and lineage within DBT, • Design and develop scalable data pipelines using Databricks and Apache Spark, • Build and optimize data workflows for batch and real-time processing, • Transform and process large datasets using PySpark, SQL, and Delta Lake, • Implement data ingestion from multiple sources (APIs, streaming, databases) Your Skills: • Python proficiency, • DBT, • AWS : Cloud formation , Service Catalog , IAM , S3 , Glue , Lambda , Knowledge python sdk, boto , EKS , ECS , ECS , VPC , SUBNETS , NACLs., • Terraform : Modules , providers , terraform enterprise , Snowflake terraform provider knowledge., • Snowflake : Snow sight , Python SDK for snowflake , Stage , storage integration , Data marketplace , direct shares , listings , catalog linked database , Apache Iceberg , external tables , Catalog integrations , Snowpipe , external volume , Cortex ai ,privatelink., • Airflow : Dag creation , operators , connections , deployment on Kubernetes , Astronomer. We are a Disability Confident Employer: Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who: • Declare they have a disability, and Make It Real (what does it mean for you): • You’d be joining an accredited Great Place to work for Wellbeing in 2024. Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce a critical component for us to achieve our organisational ambitions., • To help support wellbeing we have trained ‘Mental Health Champions’ across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy., • You will be empowered to explore, innovate, and progress. You will benefit from Capgemini’s ‘learning for life’ mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard ManageMentor, Cybersecurity qualifications and much more., • You will be joining one of the World’s Most Ethical Companies®, as recognised by Ethisphere® for 13 consecutive years. We live our values by making ethical business choices every day. Working ethically is at the centre of our culture at Capgemini, meaning you will be helping to create a future we can all be proud of. Why you should consider Capgemini: Growing clients’ businesses while building a more sustainable, more inclusive future is a tough ask. When you join Capgemini, you’ll join a thriving company and become part of a collective of free-thinkers, entrepreneurs and industry experts. We find new ways technology can help us reimagine what’s possible. It’s why, together, we seek out opportunities that will transform the world’s leading businesses, and it’s how you’ll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you’ll build the skills you want. You’ll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making the world a better place rarely is. About Capgemini: Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organisations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion. Make it real | If interested and for immediate consideration, please send your CV asap.

Role: Data Engineer Location: Glasgow/London We’re partnering with a global leader in renewable energy, driven by a clear mission: to accelerate the transition to affordable, zero-carbon power worldwide. This is a business tackling some of the most complex challenges in energy today, combining deep industry expertise with cutting-edge digital solutions. At the heart of that is data. They’re investing heavily in their digital capabilities and building a team of ambitious engineers who want to make a real-world impact. You’ll be joining a collaborative, international environment where learning, progression, and innovation are genuinely encouraged. The Role As a Data Engineer, you’ll play a key role in building and scaling modern data platforms that power critical decision-making across renewable energy assets. Working within a growing digital function, you’ll help design and develop data pipelines and lakehouse solutions that support analytics, reporting, and machine learning initiatives. This is a hands-on role with plenty of scope to learn, contribute ideas, and grow your expertise—particularly within the Databricks ecosystem. What You’ll Be Doing • Building and maintaining robust, scalable data pipelines, • Supporting the development of modern lakehouse architectures (e.g. Delta Lake), • Collaborating with engineers, analysts, and product teams to deliver high-quality data solutions, • Ensuring data quality, reliability, and performance through testing and monitoring, • Contributing to best practices across data engineering and cloud platforms, • Supporting CI/CD and DevOps approaches for data workflows, • Keeping up to date with emerging tools and technologies in the data space Knowledge & Experience • Experience working in data engineering, ideally within cloud-based environments, • Exposure to Databricks or similar modern data platforms, • Understanding of data modelling, warehousing, and pipeline design, • Familiarity with batch and/or streaming data processing, • Awareness of data governance and best practices Technical Skills • Strong Python and SQL skills, • Experience building ETL/ELT pipelines, • Exposure to orchestration tools (e.g. workflows, dbt, or similar), • Experience with version control and CI/CD tooling is a plus Why Join? • Work on meaningful projects that directly impact the future of clean energy, • Be part of a fast-growing, globally connected team, • Learn from experienced engineers and develop your skillset in a supportive environment, • Access to a competitive salary and comprehensive benefits package, • Clear opportunities for career progression as the team continues to scale This is a great opportunity for someone looking to step into a role where they can build, learn, and make an impact, without needing to already be at a senior level. If you're interested, please apply below:

Staff Machine Learning Engineer – | 3 Roles | UK Remote I'm working with a fast-growing, PE-backed SaaS business that has just launched a world-leading AI product — and they're expanding their AI/ML engineering team with three Staff-level hires. All three roles sit on the same product, the same stack, and the same mission. The difference is your specialism. ────────────────────────── 𝟭. Staff SE – Agentic AI Leading the design of multi-agent systems and LLM orchestration patterns. If you've built and shipped complex agentic workflows end-to-end, this one's for you. ▸ LangGraph · Pydantic AI · Agent SDK · LLMOps 𝟮. Staff SE – Information Extraction Owning ML models and pipelines that extract structured knowledge from complex, unstructured documents at scale. ▸ NLP · Document AI · Data Pipelines · Evals 𝟯. Staff SE – MLOps / DevOps for AI Shaping the infrastructure behind model serving, training pipelines, LLMOps, and AgentOps across the full AI stack. ▸ MLFlow · Databricks · Datadog · Terraform ────────────────────────── What all three roles require: • 7+ years in AI/ML engineering, shipping models in production, • 3+ years in a Staff-level or senior technical leadership role, • Hands-on AWS (Bedrock, SageMaker) and/or GCP Vertex AI, • Strong Python; Java or Rust a bonus, • Experience with LLMs, evaluation frameworks, and agentic AI patterns, • Docker, K8s, Terraform, CI/CD, • A collaborative leadership style — mentoring engineers, shaping best practices ────────────────────────── Core stack: Python · Rust · Java · Amazon Bedrock · SageMaker · Vertex AI · LangGraph · Pydantic AI · LangFuse · MLFlow · Databricks · Datadog · Claude Code · Docker · K8s · Terraform · Vector DBs · Graph DBs ────────────────────────── UK Remote Competitive Salary and benefits Not eligible for visa sponsorship ────────────────────────── Interested? Please apply, or know someone who might be? Drop me a DM • Seniority Level, • Not Applicable, • Industry, • Software Development, • Employment Type, • Full-time, • Job Functions, • Engineering, • Skills, • Artificial Intelligence (AI), • Large Language Models (LLM), • Machine Learning, • Technical Leadership, • Multi-agent Systems, • AWS SageMaker, • Amazon Web Services (AWS), • Python (Programming Language), • LangGraph, • Amazon

The Opportunity - (Fully Remote, Perm role) This is a greenfield data platform build. ___ is in the middle of a major AI transformation — a multi‐agent copilot platform (KAI) is already live in production, serving manufacturing clients globally. The AI roadmap is ambitious (agentic AI capabilities, multi‐agent orchestration, voice interfaces), and the next wave of capabilities depends on a strong data engineering foundation. A Databricks lakehouse POC is being evaluated (Unity Catalog, Delta Sharing, PrivateLink to RDS), and the team is assessing the right long‐term analytics platform strategy. This role builds the entire data engineering function from scratch — defining the architecture, tooling, and patterns that power the next generation of AI capabilities. This is an entirely forward‐looking role. While there is an active platform modernisation underway (the engineering team is migrating a .NET platform from SQL Server to PostgreSQL and containerising for Kubernetes), this role’s primary focus is building new data pipelines and analytics infrastructure, not maintaining legacy systems. That said, collaboration with the platform engineering team is important, as the data pipelines need to ingest from both the existing SQL Server estate and the new PostgreSQL databases. Core Technical Requirements • Python — primary language for data pipelines, scripting, and integration with the AI stack. This is a Python‐first team, • SQL (SQL Server + PostgreSQL) — deep experience required across both engines. The platform runs a large‐scale multi‐tenant database estate with per‐client schemas (local, global, corporate). The new platform targets Aurora PostgreSQL, with several modules already migrated. Pipelines must bridge both., • Databricks / Apache Spark — a lakehouse POC is being evaluated with Unity Catalog and Delta Sharing via AWS PrivateLink. Experience with Databricks or equivalent analytics platforms is important for assessing and scaling the right approach, • Apache Kafka — event streaming experience is essential. The platform is evaluating Kafka as the strategic backbone for ordered event logs, consumer group replay, and guaranteed partition ordering as the microservices fleet scales, • ETL/ELT pipeline design — building and maintaining pipelines into a medallion architecture (bronze/silver/gold layers) on Databricks or equivalent analytics platform, • Delta Lake — understanding of lakehouse table formats, time travel, and ACID transaction patterns, • AWS data services — RDS, S3, Lambda, Glue or equivalent. The platform runs entirely on AWS • Linux / CLI proficiency — must be comfortable working AI-Assisted Development Methodology -> Solvace is transitioning towards AI‐assisted development as a core engineering practice. Candidates should demonstrate: • Hands‐on experience with AI coding tools — Claude Code, OpenAI Codex, GitHub Copilot, Cursor, or similar. We’re looking for engineers who have integrated these tools into their professional workflow, not just experimented casually, • Spec‐driven development — ability to write clear technical specifications that can be used to drive both human and AI‐assisted implementation, with strong evaluation criteria and test coverage, • Portfolio evidence — professional projects or side projects that demonstrate AI‐assisted development practices. Contributions to or experimentation with emerging projects like OpenClaw are a strong signal, • Testing and evaluation rigour — experience building robust test suites, automated quality gates, and evaluation frameworks that ensure AI‐assisted code meets production standards Nice-to-Have -> • Apache Flink — for real‐time stream processing as the platform moves from batch to streaming analytics, • Apache Iceberg — experience with open table formats alongside or as an alternative to Delta Lake, • Go or Rust — valued as evidence of strong backend engineering and systems thinking, even though Python is the primary language, • Multi‐tenant data architectures — the platform runs per‐client schemas with tenant isolation requirements. Understanding tenant isolation patterns is a significant advantage, • Terraform / IaC — infrastructure is managed via Terraform; the Databricks POC has been codified in Terraform, • dbt or similar transformation framework, • Manufacturing / industrial data domain experience (sensor data, quality metrics, OEE, SPC), • CDC (Change Data Capture) — the platform is building CDC pipelines for the SQL Server to PostgreSQL transition, • Weaviate or other vector database experience — currently used for semantic search in the AI agent layer Why Join? • Greenfield data platform — the entire data engineering practice needs to be built from scratch. A lakehouse POC is being evaluated but the production architecture is theirs to define — patterns, tooling, and platform decisions from day one, • Direct AI impact — every pipeline they build directly unblocks AI agent capabilities. The KAI copilot is live in production and evolving towards agentic AI — autonomous agents that take actions, orchestrate workflows, and operate across systems. This role provides the data foundation that makes agentic capabilities possible, • Event streaming architecture — opportunity to design and implement a Kafka‐based event backbone, shaping the platform’s real‐time data architecture, • Manufacturing AI — opportunity to work at the intersection of industrial operations and generative AI, a domain with massive untapped potential. Rich, real‐world data: quality inspections, KPIs, maintenance records, safety observations, process parameters across global manufacturing sites, • Small team, high autonomy — the Innovation Hub operates with startup‐level autonomy inside a funded, growing company, • Leadership trajectory — the data function is critical to the platform and will grow. As an early hire, there is an open career path that will grow with the function — earned, not guaranteed

Contract Machine Learning Engineer Duration: Initially 3 months Day rate: £500, Inside IR35 Workplace: Remote, with occasional travel to client-site Inara are supporting a consultancy-led team delivering production-grade machine learning platforms for a range of end clients, and they’re looking for a senior, hands-on Contract ML Engineer to help take ML systems from experimentation into reliable, scalable production. This role is firmly focused on ML enablement and platform engineering rather than model research. You’ll be the person ensuring models can be trained, tracked, deployed, governed, and monitored properly in real-world environments. What you’ll be doing • Designing and building end-to-end MLOps platforms that support the full ML lifecycle, • Implementing and operating MLflow for experiment tracking, model registry, and versioning, • Enabling production deployments of ML models (batch and/or real-time), • Putting robust CI/CD pipelines in place for ML workflows, • Partnering closely with Data Scientists to move models from notebooks into production, • Establishing best practices around model governance, monitoring, retraining, and environments, • Integrating ML platforms with Databricks and cloud-native services What we’re looking for • Strong, real-world MLOps experience (this is not a theoretical role), • Deep hands-on MLflow experience — this is essential, • Proven track record of productionising ML models across multiple client or project environments, • Background in one or more of:, • MLOps / ML Engineering, • DevOps with ML platforms, • Data Science with a strong production focus, • Experience designing, supporting, and operating ML systems in production Technical environment (experience expected across most of these) • Python (expert-level), • Databricks, • Cloud platforms (AWS preferred; SageMaker exposure a bonus), • CI/CD for ML workloads, • Docker and Kubernetes, • Infrastructure as Code (Terraform or similar)

Lead Data Platform Engineer UK Remote Salary: £80,000 - £85,000 This is an opportunity to step into a highly influential Data Platform Engineering role where you will shape, optimise and own a modern Databricks Lakehouse environment. You will play a key role in driving engineering best practice, improving automation and enabling scalable data solutions across a growing data function. The Company They are a large, well‑established organisation known for combining deep technical expertise with a people‑first culture. With a nationwide presence and a modern approach to flexible working, they invest heavily in technology, innovation and colleague development. Their data function is expanding and plays a central role in supporting transformation, decision‑making and future AI initiatives. You will join a collaborative team that values engineering excellence, autonomy and continuous improvement. The Role As Lead Data Platform Engineer, you will: • Develop and deploy Databricks Lakehouse platform solutions within Azure., • Build and maintain automation for clusters, tagging, monitoring and platform operations., • Architect and design end‑to‑end data platform solutions focused on scalability, security and reliability., • Lead delivery using Databricks, PySpark, Spark SQL and Azure Data Factory., • Drive DevOps best practices including CI/CD, automated testing and infrastructure as code., • Collaborate closely with data engineers, ML engineers and wider technical teams to deliver robust platform capabilities., • Take ownership of key data platform projects and influence engineering direction., • Provide technical leadership and ensure standards, patterns and best practices are followed. Your Skills and Experience You will bring: • Strong commercial experience in Azure and Databricks, with deep knowledge of Lakehouse architecture., • Proficiency in PySpark, Python, SQL and Spark SQL., • Strong DevOps engineering skills including CI/CD, automated testing and deployment pipelines., • Experience with monitoring, logging and alerting solutions., • Ability to design, build and optimise cloud platform solutions., • Stakeholder management skills and confidence working across multiple teams., • API development experience., • Azure Data Factory knowledge is beneficial. What They Offer • Salary between £80,000 and £85,000 plus bonus., • Comprehensive benefits package and annual pay review., • Flexible by choice working environment with remote‑first culture., • 35‑hour working week promoting genuine work‑life balance., • Opportunities to shape platform strategy and contribute to future AI and automation initiatives. How to Apply If you are a strong Data Platform Engineer with deep Databricks expertise and want to take ownership of a modern Azure Lakehouse environment, please apply today.

About the Role We’re partnered with a growing, data-led technology business that is scaling its data capabilities and investing heavily in how data is structured, accessed and used across the organisation. We are looking for a Data Analyst with experience in Analytics Engineering & BI Development with strong SQL expertise at the core of their skillset. This role sits at the intersection of data engineering and business intelligence, combining hands-on data transformation with impactful reporting and visualisation. You’ll play a key role in shaping how data is modelled, consumed and leveraged by teams across the business, enabling better and faster decision-making. The Opportunity This role is ideal for someone who: • Enjoys working deeply with data using SQL, • Wants ownership over how data is structured and delivered, • Is comfortable bridging technical and business teams, • Likes seeing their work directly influence commercial and operational decisions Key Responsibilities • Design and develop scalable data models within a cloud-based data warehouse, • Write, optimise, and maintain complex SQL queries for data transformation and analysis, • Build clean, reliable datasets to support reporting and analytics use cases, • Develop dashboards and reports using modern BI tools, • Translate business requirements into clear, user-friendly data outputs, • Partner with stakeholders across product, commercial, and operations teams, • Implement data quality checks to ensure accuracy and consistency, • Improve performance of queries, pipelines, and reporting outputs, • Identify opportunities to automate and streamline data processes What We’re Looking For Core Experience (Essential) • Strong SQL skills (this is critical) — proven ability to write complex queries (CTEs, window functions, optimisation, performance tuning), • Experience building and maintaining data models for analytical use, • Background in a BI / Analytics Engineering / Data Analyst type role, • Hands-on experience with at least one major BI tool (e.g. Tableau, Power BI, Looker, etc.), • Experience working with cloud data platforms (e.g. Snowflake, BigQuery, Redshift, Databricks), • Understanding of ETL/ELT processes and data transformation workflows, • Experience working with non-technical stakeholders and translating requirements Nice to Have • Experience with modern data transformation tools (e.g. dbt or similar), • Exposure to workflow orchestration tools, • Familiarity with version control (e.g. Git) Key Skills & Attributes • Highly analytical with strong problem-solving ability, • Excellent attention to detail, particularly around data accuracy, • Strong communication skills — able to explain complex data clearly, • Commercial awareness and ability to link data to business outcomes, • Proactive mindset with a sense of ownership, • Collaborative approach, working effectively across teams The Package • Up to £65K base salary, • Private Health and Dental, • Generous Pension scheme, • Income protection, • Many other great benefits... Why Join? • Opportunity to shape and influence a growing data function, • High-visibility role with direct impact on business decisions, • Modern data stack and strong investment in data capabilities, • Flexible working environment (remote or hybrid available), • Collaborative, forward-thinking culture, • Vast amounts of career opportunities

AI Engineer Job Tenure: Full-time, permanentSalary: CompetitiveCompany Description Ready to join a team thats leading the way in reshaping the future of insurance? Here at esure Group, we are on a mission to revolutionise insurance for good! We’ve been providing Home and Motor Insurance since 2000, with over 2 million customers trusting us to keep them covered through our esure and Sheilas’ Wheels brands. With a bold dedication for digital innovation, were transforming the way the industry operates and putting customers at the heart of everything we do. Having completed our recent multi-year digital transformation, we’re now leveraging advanced technology and data-driven insights alongside exceptional service, to deliver personalised experiences that meet our customers ever-changing needs today and in the future. Job Description We currently have a phenomenal opportunity for an AI Engineer to join our us as we enhance our customer experience by harnessing the power of NLP, large language models, and flawless integration with third-party GenAI services. In this dynamic role, youll be involved in every stage of the AI lifecycle, from brainstorming ideas and crafting prompts to fine-tuning models and deploying them into production. Success in this role is measured through rigorous A/B testing, ensuring our solutions deliver real value. Youll have the opportunity to work on a variety of impactful projects across the entire enterprise. We are seeking an innovative individual who shares our vision to fix insurance for good. What you’ll do: Collaborate with business partners to identify use-cases where GenAI can provide measurable benefits. Support the data science and AI team in deploying scalable AI applications across the enterprise. Work with a multi-functional team (DevOps, data engineers, developers, testers, Infosec) to productionize AI services on AWS. Enhance our tech stack, including MLOps, CI/CD pipelines, UI, and AI Python libraries. Develop prompts, fine-tune models, and track results. Evaluate third-party GenAI and LLM technologies for cost-benefit analysis. Deliver projects from scoping and R&D to production deployment and benefit measurement. Follow and contribute to standards for code quality, R&D, and model development. Engineer data for optimal AI application performance. Advise peers and senior management on business and customer impact. Write production-grade Python code, leveraging CI/CD, Databricks, and ensuring appropriate test coverage; proficiency in SQL. Liaise with third-party partners and stay updated on field advancements and regulations. Collaborate with data governance and data management teams on data requirements. Qualifications What we’d love you to bring: You are a self-starter with experience in delivering research + models to production to drive tangible commercial benefits and improved customer experiences. You thrive in working autonomously and collaboratively to drive impact in a fast-paced multi-functional business. PhD or MSc experience in a numerate subject: Machine Learning, Computer Science, Statistics, or equivalent, Demonstrable experience of applying, researching, and developing sophisticated NLP models, prompt engineering + fine-tuning LLMs to drive value in a commercial setting, Able to work independently and efficiently to deliver projects on time, taking project briefs and refining them to strong results. Experienced in engaging with non-technical stakeholders to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. Knowledge of Langchain, huggingface and LLM offerings by 3rd party vendors. Knowledge of OO programming and software design, i.e., SOLID principles. Knowledge and working experience of AGILE methodologies. Familiarity with Databricks, and RAG application architecture a plus Experience with latency optimisation and quantisation preferred Additional Information What’s in it for you?: Competitive salary that reflects your skills, experience and potential. Discretionary bonus scheme that recognises your hard work and contributions to esure’s success. 25 days annual leave, plus 8 flexible days and the ability to buy and sell further holiday. Our flexible benefits platform is loaded with perks to choose from, so you can build a personal toolkit to support your health, wellbeing, lifestyle, and finances. Company funded private medical insurance for qualifying colleagues. Fantastic discounts on our insurance products! 50% off for yourself and spouse/partner and 10% off for direct family members. We’ll elevate your career with hands-on training, mentoring, access to our exclusive academies, regular career conversations, and expert partner resources. Driving good in the world couldn’t be more important to us. Our colleagues can use 2 volunteering days per year to support their local communities. Join our internal networks and communities to connect, learn, and share ideas with likeminded colleagues. We’re a proud supporter of the ABI’s ‘Make Flexible Work’ campaign and welcome you to ask about the flexibility you need. Our hybrid working approach also puts you in the driving seat of how and where you do your best work. And much more; See a full overview of our benefits here Reward and benefits | Esure Group PLC We are committed to creating an inclusive and diverse workplace where everyone feels valued, respected, and empowered. We celebrate individuality and create spaces where unique backgrounds and experiences can come together. We believe that diverse perspectives drive innovation, in turn enabling us to better serve our customers, community and build a stronger organisation. Our commitment to inclusion extends to every part of our business, from hiring practices to professional growth opportunities, ensuring equal access and support for all.

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible by building and deploying big data pipelines and reporting datastores on the Data Lake and Data Bricks, driven by web applications using React, Spring Boot, Java, and AWS. Experienc

Drive Kubernetes-based runtime standards and enforce SRE/operability guardrails. Hands‑on experience with Kubernetes (EKS or equivalent), deploying microservices, and service‑to‑service networking.

A leading global financial institution in Glasgow is looking for a Data Engineer III to design and maintain scalable data pipeline solutions using Databricks, Python, and AWS. The ideal candidate will have strong data engineering skills, with experience in processing large datasets and optimizing da

Manage and develop a team of data scientists, setting standards for technical excellence, delivery discipline, and stakeholder engagement. AWS, Azure, GCP or Databricks) and modern ML/MLOps practices. Proven track record managing and growing high‑performing data science teams, including technical

This is a full-time position with a fixed-term contract of 24 months.

A leading renewable energy company in Scotland is looking for a skilled Data Engineer to join their asset performance management team.

Champion cloud architecture on AWS, including networking, compute, storage, security, and cost governance. Proficiency in AWS services including IAM, VPC, EC2/EKS, S3, Lambda, Step Functions, and CloudWatch.

In this role, you will design and maintain scalable data solutions, utilizing technologies such as Databricks, Python, and AWS.

This role sits within the Data Science team of the Commercial function of Business Energy and focuses on delivering data science solutions using machine learning, AI and optimisation. Data engineering and analytics skills using PySpark or Spark SQL in Azure Databricks. Understanding of delta lake /

Drive Kubernetes-based runtime standards and enforce SRE/operability guardrails. Hands-on experience with Kubernetes (EKS or equivalent), deploying microservices, and service-to-service networking.

As a Data Engineer III at JPMorganChase within the External Regulatory Financial Control (ERFC) Technology team, you will play a crucial role in designing, developing, and maintaining scalable data pipeline solutions using Databricks, Python/PySpark on AWS. Design, develop, and maintain robust data

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Fra

Candidates should have extensive experience in data engineering and a solid track record with Databricks projects. A leading technology firm is seeking an experienced Solutions Architect specializing in Databricks to work on fully remote contracts.

The ideal candidate will have strong skills in Python and SQL, along with hands-on experience in Azure Databricks.

Join a forward-thinking technology consultancy that champions innovation and collaboration.This exciting opportunity involves developing scalable data pipelines, utilizing cutting-edge technologies like AWS and Python, and working closely with cross-functional teams to drive data solutions.As part o

DATAPAO, meaning that you'll get access to Databricks' public and internal courses to learn all the tricks of Distributed Data Processing, MLOps, Apache Spark, Databricks, and Cloud Migration from the best. Based on your understanding, you will recommend solutions that leverage Databricks or native

SC Cleared – Cloud Engineer (Databricks / Azure). Build and maintain data processing and transformation workflows using Databricks. Strong hands‑on Databricks experience in production environments.

As a Data Engineer III at JPMorganChase within the External Regulatory Financial Control (ERFC) Technology team, you will play a crucial role in designing, developing, and maintaining scalable data pipeline solutions using Databricks, Python/PySpark on AWS. Design, develop, and maintain robust data

A leading technology services provider seeks a Data Engineer (Databricks Specialist) to work in Erskine, Newcastle, or London. You will build scalable data pipelines and manage Databricks environments while collaborating on innovative AI projects. The ideal candidate has 6+ years of experience, stro

The successful candidate will architect and design robust data platforms using tools such as Databricks and Azure Data Factory, ensuring scalability and compliance.

Ideal candidates will have over 8 years of experience in Data Engineering and strong skills in SQL, Databricks, and pipeline development.

DATAPAO, meaning that you'll get access to Databricks' public and internal courses to learn all the tricks of Distributed Data Processing, MLOps, Apache Spark, Databricks, and Cloud Migration from the best. You have a proven track record working with Databricks. Databricks Workflows, DLT, Airflow, A

A European consultancy is seeking a Databricks-focused Machine Learning Engineer for a contract role in the United Kingdom. The ideal candidate will have strong expertise in Databricks, DevOps practices, and excellent communication skills.

A leading tech consultancy is seeking a SC Cleared Cloud Engineer specializing in Databricks and Azure to join their remote team. Candidates must have strong hands-on experience with Databricks and an active SC clearance or eligibility to obtain one.

Experience with Databricks Workflows/Jobs, Unity Catalog, and Delta Live Tables. Build scalable Spark jobs on Databricks, optimize performance, and enforce coding standards. Advanced experience with Apache Spark and Databricks, including job optimization and Delta Lake patterns.

Provide technical leadership in Databricks implementations, migrations, and integrations with client systems. Collaborate closely with Databricks engineering, project managers, and client teams to meet delivery objectives. Databricks Certified at Professional or Champion level.

Valcon is growing its Databricks community and we’re looking for a Databricks Architect to help clients turn data into measurable business results. As a Databricks Elite Partner, we work on some of the most advanced data and AI projects in Europe. You’ll own the design and governance of the Data

As a Data Engineer III at JPMorganChase within the External Regulatory Financial Control (ERFC) Technology team, you will play a crucial role in designing, developing, and maintaining scalable data pipeline solutions using Databricks, Python/PySpark on AWS. Design, develop, and maintain robust data

A leading European consultancy in the UK is seeking a Databricks Architect to help clients use data for measurable business results. You will work on advanced data and AI projects, owning the design and governance of data solutions, and collaborating closely with partners at Databricks.

This role involves delivering complex projects across various industries using Databricks and managing customer relationships.

A leading data and AI company based in the United Kingdom is seeking a skilled Security Lead to integrate security into their core platforms.The ideal candidate will lead teams, shape security architecture, and foster a culture of proactive security among engineers.Responsibilities include building

A leading data solution provider in the UK is seeking a Databricks Architect to design and deliver modern Lakehouse solutions. The ideal candidate should have deep experience with Databricks and cloud technologies, along with excellent communication skills.

A global financial services leader is seeking a Data Engineer III to design and maintain scalable data pipelines using Python and PySpark on the Databricks platform.

Build and maintain scalable data pipelines using Databricks. Manage and optimize Databricks Workspace, Clusters, Jobs, Repos, and Delta Live Tables. Proven experience with Databricks and its ecosystem.

A leading recruitment agency is looking for an experienced Power BI Developer to join a major UK retailer on a 6-month contract.The role involves designing, developing, and optimizing Power BI datasets and dashboards while collaborating with data engineers and business analysts.Ideal candidates will

Databricks Engineer – Fully remote – 6‑month contract – £550‑£650 per day – Outside IR35. Building and optimising Databricks pipelines. Strong Databricks and PySpark experience.

A specialist data and AI consultancy in the United Kingdom is hiring a Resident Solutions Architect to lead their Databricks engagements. This hands-on, client-facing role requires a candidate with extensive experience in data engineering and a strong track record in delivering Databricks projects.

Databricks workloads with Repos, GitHub Actions, or Azure DevOps. Deep experience architecting and delivering enterprise-scale Databricks solutions end‑to‑end. You’ll work with enterprise clients to architect scalable, secure, high‑performance data platforms using Databricks and cloud-native

The ideal candidate will have strong experience in Databricks and PySpark, and will be responsible for building and optimising Databricks pipelines, supporting data migration, and collaborating with architects on solutions. A technology consulting firm in the UK is seeking a Databricks Engineer for

You will design and maintain data pipelines using Python and PySpark on Databricks, while collaborating with cross-functional teams to support business objectives.