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.