Glasgow
Employment Type: engagement is inside IR‑35 through an umbrella company Requirements 'must have': • Education: Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience)., • 4+ years of experience developing data pipelines and data warehousing solutions using Python and libraries such as Pandas, NumPy, PySpark, etc., • 3+ years hands-on experience with cloud services, especially Databricks, for building and managing scalable data pipelines, • 3+ years of proficiency in working with Snowflake or similar cloud-based data warehousing solutions, • 3+ years of experience in data development and solutions in highly complex data environments with large data volumes., • Solid understanding of ETL principles, data modelling, data warehousing concepts, and data integration best practices-Familiarity with agile methodologies and the ability to work collaboratively in a fast-paced, dynamic environment., • Experience with code versioning tools (e.g., Git), • Knowledge of Linux operating systems, • Familiarity with REST APIs and integration techniques, • Familiarity with data visualization tools and libraries (e.g., Power BI), • Background in database administration or performance tuning, • Familiarity with data orchestration tools, such as Apache Airflow, • Previous exposure to big data technologies (e.g., Hadoop, Spark) for large data processing, • Strong analytical skills, including a thorough understanding of how to interpret customer business requirements and translate them into technical designs and solutions., • Strong communication skills both verbal and written. Capable of collaborating effectively across a variety of IT and Business groups, across regions, roles and able to interact effectively with all levels., • Self-starter. Proven ability to manage multiple, concurrent projects with minimal supervision. Can manage a complex ever changing priority list and resolve conflicts to competing priorities., • Strong problem-solving skills. Ability to identify where focus is needed and bring clarity to business objectives, requirements, and priorities. Requirements 'nice to have': • Experience in financial services, • Knowledge of regulatory requirements in the financial industry Tasks: • Collaborating with cross-functional teams to understand data requirements, and design efficient, scalable, and reliable ETL processes using Python and Databricks, • Developing and deploying ETL jobs that extract data from various sources, transforming them to meet business needs., • Taking ownership of the end-to-end engineering lifecycle, including data extraction, cleansing, transformation, and loading, ensuring accuracy and consistency., • Creating and managing data pipelines, ensuring proper error handling, monitoring and performance optimizations, • Working in an agile environment, participating in sprint planning, daily stand-ups, and retrospectives., • Conducting code reviews, providing constructive feedback, and enforcing coding standards to maintain a high quality., • Developing and maintaining tooling and automation scripts to streamline repetitive tasks., • Implementing unit, integration, and other testing methodologies to ensure the reliability of the ETL processes, • Utilizing REST APIs and other integration techniques to connect various data sources, • Maintaining documentation, including data flow diagrams, technical specifications, and processes., • Designing and implementing tailored data solutions to meet customer needs and use cases, spanning from streaming to data lakes, analytics, and beyond within a dynamically evolving technical stack., • Collaborate seamlessly across diverse technical stacks, including Databricks, Snowflake, etc., • Developing various components in Python as part of a unified data pipeline framework., • Contributing towards the establishment of best practices for the optimal and efficient usage of data across various on-prem and cloud platforms., • Assisting with the testing and deployment of our data pipeline framework utilizing standard testing frameworks and CI/CD tooling., • Monitoring the performance of queries and data loads and perform tuning as necessary., • Providing assistance and guidance during QA & UAT phases to quickly confirm the validity of potential issues and to determine the root cause and best resolution of verified issues., • Adhere to Agile practices throughout the solution development process., • Design, build, and deploy databases and data stores to support organizational requirements.