Principal Data Engineer

Are you ready to shape the future technological landscape in Europe?
We are dedicated to responsible digitalisation, building innovative, inclusive solutions that drive meaningful impact. With over 8,900 professionals across Europe, we help EU institutions, public and private organisations thrive in a rapidly evolving digital world. Are you ready to shape the future through technology? Your journey starts here. Take a look at some of our impactful projects here: https://netcompany.com/cases/

Responsibilities

Ever wondered what it feels like to be a Principal Data Engineer in Netcompany ?; As a Principal Data Engineer you will:; Lead and grow multiple delivery teams of Cloud Data Management and Data Lake Engineers, managing Leads and Engineering Managers, setting technical direction and coaching at scale.; Own a portfolio of client engagements end-to-end — delivery quality, commercial health, risk, and strategic alignment.; Shape technical strategy and architecture standards for cloud-native data lakes and lakehouses (Delta Lake, Apache Iceberg) on Azure, AWS or Databricks, and drive AI-powered transformation across the practice — including how AI coding assistants and agentic workflows reshape delivery.; Lead pre-sales and commercial activities: solution design, technical estimations, bids, and client conversations.; Partner with the Head of Data Management and BI Engineering on practice growth — hiring, capability roadmap and market positioning — and build cross-practice partnerships with AI/ML, BI and application leadership.; Champion engineering excellence and DataOps maturity — CI/CD for data, IaC, security, observability and governance.

Requirements

What would make you a fit for the role:; Senior-level experience in data engineering / cloud data management, including experience managing managers or leads.; Hands-on architecture experience across at least one major cloud data platform — Azure, AWS or Databricks — including data lake / lakehouse design.; Solid technical credibility with SQL, Python, Spark and workflow orchestration — comfortable going deep in design reviews when needed.; Experience setting standards for performance, cost, security and data quality across multiple engagements.; Strong communication and coaching mindset for the Leads you grow.; Bachelor’s or Master’s degree in Computer Science, Data Engineering, Data Science or a related field. It would also be a plus if you match some of the following:; Hands-on with AI coding assistants and agentic tools (e.g. Claude Code, Copilot-class tools, LLM-based agents).; Experience with GenAI / ML enablement patterns on top of data platforms — vector stores, RAG architectures.; Experience with data governance platforms (Unity Catalog, Microsoft Purview, Collibra or Atlan).; Experience with dbt for in-warehouse / in-lakehouse transformations, or exposure to Microsoft Fabric.; Familiarity with streaming technologies, Kubernetes, or DevOps / IaC tooling.