ppOur 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. /p pWe 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. /p pThis is a hands‑on role for someone who takes ownership, cares deeply about data integrity, and is comfortable working across the full data stack. /p h3Conditions /h3 ul liPermanent contract /li liHybrid model: 1 day of remote work per week /li liWorking hours: 9:30 a.m. to 6:30 p.m. (Fridays until 2:30 p.m.) /li /ul h3Mission of the role /h3 pDesign, build, and maintain a robust, scalable, and validation‑first data infrastructure that ensures high‑quality, reliable data across the industrial digital platform. /p pYou will act as a key contributor to data architecture and governance, ensuring that data is accurate, accessible, and trusted across all business functions. /p h3Key responsibilities /h3 h3Data Quality Governance /h3 ul liDefine and enforce validation standards across all data systems /li liEnsure data accuracy, consistency, and integrity from ingestion to consumption /li liDesign and maintain data contracts, lineage tracking, and cataloguing practices /li liDesign, build, and maintain scalable data pipelines with validation embedded at every stage /li /ul h3ETL/ELT Development /h3 ul liBuild and evolve ETL/ELT processes with automated quality checks /li liEnsure issues are detected and resolved before reaching downstream users /li /ul h3Cross‑functional collaboration /h3 ul liTranslate complex requirements from engineers, analysts,



and scientists into robust solutions /li liWork closely with multiple teams to deliver production‑grade data systems /li liOptimise database performance and storage architecture /li liEnsure continuous reliability and efficiency of data systems /li liMonitor pipeline health and proactively detect issues /li liDiagnose failures quickly and ensure continuous data availability /li liStay up to date with data engineering trends and tools /li liIntroduce improvements that add real value to the platform /li /ul h3Profile /h3 ul li6+ years of experience in data engineering, ideally in industrial or operational environments /li liStrong SQL skills and hands‑on ETL/ELT experience with a focus on data quality /li liProficiency in Python, Java, or Scala /li liSolid understanding of data modelling, data warehousing, and big data technologies (Spark, Hadoop) /li liProven experience with Azure and Databricks /li liExperience in data governance (cataloguing, lineage, metadata, access control) /li liFamiliarity with data quality tools (Great Expectations, dbt tests, Soda) /li liDegree in Computer Science, Engineering, or a related field /li liStrong problem‑solving skills and attention to detail /li liExcellent communication skills across technical and non‑technical teams /li /ul h3Nice to Have /h3 ul liExperience building and optimising data lakes and warehouses in Azure /li liReal‑time and streaming data processing (Event Hubs, Stream Analytics) /li liExperience with data mesh or data fabric architectures /li liKnowledge of regulatory frameworks (ISO, GDPR) /li liExperience with containerisation and orchestration (Docker, Kubernetes, ADF) /li /ul h3Languages /h3 ul liSpanish – Highly valued /li liItalian – Highly valued /li /ul h3What we offer /h3 ul liStrategic role with real impact on data‑driven decision making /li liDynamic and fast‑growing environment /li liOpportunity to build and scale a modern industrial data platform /li /ul /p #J-18808-Ljbffr

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