Data Engineer - Industrial Digital Platform

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 | *****, 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