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 a.m. to 6:30 p.m. (Fridays until 2:30 p.m.)

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
- 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
- Optimise database performance and storage architecture
- Ensure continuous reliability and efficiency of data systems
- Monitor pipeline health and proactively detect issues
- Diagnose failures quickly and ensure continuous data availability
- 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

- 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

#J-18808-Ljbffr

📌 Data Analitics - Industrial Digital Platform (Madrid)
🏢 Verdalia Bioenergy
📍 Madrid