Data Engineer - Industrial Digital Platform
1 day ago
Seville
Data Engineer - Industrial Digital Platform Our Industrial Digital Platform team is looking for a Data Engineer to build and scale the data backbone that powers decision-making across engineering, operations, and leadership. We are developing a modern data platform focused on transforming industrial and operational data into a reliable, high-quality asset. This role sits at the intersection of industrial systems and cloud data technologies, with a strong emphasis on data quality, governance, and scalability. This is a hands-on role for someone who takes ownership, cares deeply about data integrity, and is comfortable working across the full data stack. Conditions • Permanent contract, • Hybrid model: 1 day of remote work per week, • Working hours: 9:30 am to 6:30 pm (Fridays until 14:30), • Location: Gta. Mar Caribe 1, Hortaleza | 28043, Madrid | Spain Mission of the role Design, build, and maintain a robust, scalable, and validation-first data infrastructure that ensures high-quality, reliable data across the industrial digital platform. You will act as a key contributor to data architecture and governance, ensuring that data is accurate, accessible, and trusted across all business functions. Key responsibilities Data Quality & Governance: • Define and enforce validation standards across all data systems, • Ensure data accuracy, consistency, and integrity from ingestion to consumption, • Design and maintain data contracts, lineage tracking, and cataloguing practices Pipeline Engineering: • Design, build, and maintain scalable data pipelines with validation embedded at every stage ETL/ELT Development: • Build and evolve ETL/ELT processes with automated quality checks, • Ensure issues are detected and resolved before reaching downstream users Cross-functional collaboration: • Translate complex requirements from engineers, analysts, and scientists into robust solutions, • Work closely with multiple teams to deliver production-grade data systems Database & Storage Optimisation: • Optimise database performance and storage architecture, • Ensure continuous reliability and efficiency of data systems Monitoring & Incident Response: • Monitor pipeline health and proactively detect issues, • Diagnose failures quickly and ensure continuous data availability Innovation: • Stay up to date with data engineering trends and tools, • Introduce improvements that add real value to the platform Profile • 6+ years of experience in data engineering, ideally in industrial or operational environments, • Strong SQL skills and hands-on ETL/ELT experience with a focus on data quality, • Proficiency in Python, Java, or Scala, • Solid understanding of data modelling, data warehousing, and big data technologies (Spark, Hadoop), • Proven experience with Azure and Databricks, • Experience in data governance (cataloguing, lineage, metadata, access control), • Familiarity with data quality tools (Great Expectations, dbt tests, Soda), • Degree in Computer Science, Engineering, or a related field, • Strong problem-solving skills and attention to detail, • Excellent communication skills across technical and non-technical teams Nice to Have • Experience building and optimising data lakes and warehouses in Azure, • Real-time and streaming data processing (Event Hubs, Stream Analytics), • Experience with data mesh or data fabric architectures, • Knowledge of regulatory frameworks (ISO, GDPR), • Experience with containerisation and orchestration (Docker, Kubernetes, ADF) Languages • English — Fluent (required), • Spanish — Highly valued, • Italian — Highly valued What we offer • Strategic role with real impact on data-driven decision making, • Dynamic and fast-growing environment, • Opportunity to build and scale a modern industrial data platform If you’re interested, feel free to apply.