job specification

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.