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

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