Senior Data Platform Engineer

Digital & Technology Team (D&T)is an integral division ofHEINEKEN Global Shared Services Center. We are committed to making Heineken the most connected brewery. That includes digitalizing and integrating our processes, ensuring best-in-class technology, and embedding a data-driven culture. By joining us you will work in one of the most dynamic and innovative teams and have a direct impact on building the future of Heineken!

Would you like to meet the Team, see our office and much more? Visit our website: Heineken (heineken-dt.pl)

Are you passionate about leveraging cutting-edge technology to shape the future of data platform engineering? Do you thrive in dynamic environments, working with modern tools like Databricks, Azure, and Apache Spark? If so, we have the perfect opportunity for you!

At Heineken, we are not just brewers of the world’s most iconic beers—we are a data-driven company that values innovation and continuous improvement. As aSenior Data Platform Engineerin our Global Platform Team, you will play a crucial role in driving our data strategies and transforming how we manage, process, and analyze large-scale data.

Your responsibilities would include:

• designing and building scalable data processing frameworks that support both streaming and batch workloads, aligning with our metadata-driven architecture
• working on big data using PySpark and SQL, optimizing data pipelines and contributing to the development of our modern Data Lakehouse built on the medallion architecture
• collaborating with cross-functional teams to create seamless ETL/ELT processes and drive performance optimization using techniques like Delta optimization, Z-ordering, and liquid clustering
• taking ownership of building efficient and scalable solutions leveraging the latest trends in Databricks, including Structured Streaming, Lakeflow Declarative Pipelines, Unity Catalog, and DBSQL
• collaborating using Git, working in a fast-paced, agile environment, and continuously refining our common code base.

You are a good candidate if you have:

• 5+ years of experience in data/software engineering roles, with hands-on experience in building and maintaining data frameworks for large-scale distributed data processing
• excellent Python and software development skills, including OOP principles and familiarity with Python testing libraries like pytest/unittest
• the ability to write elegant and maintainable code (knowledge of pylint/pyright is a plus)
• experience with following python libraries: Pydantic, SQLGlot
• proficiency with building data pipelines using Pyspark including performance observability and tuning
• Databricks skills: Proficiency in building data pipelines (batch/streaming) using Lakeflow Declarative Pipelines (DLT) and Job-based orchestration. Familiarity about Unity Catalog. Comfortable staying on top of latest advancements in Databricks platform
• Strong knowledge of data ingestion techniques, data warehousing, medallion architecture, and performance optimization for big data.
  knowledge about version control, standard approaches like gitflow, trunk-based, application in GitHub, GitLab, Azure Devops

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