Data Analitics

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