Digital & Technology Team (D&T) is an integral division of HEINEKEN 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)
The role in as part of the European Data & AI Hub within the D&T department of HEINEKEN International is critical in Heineken to operationalise our strategy of standardised and scalable data foundations across the region and enterprise.
Chapter Lead- Data Engineer will work with colleagues across Heineken as part of a team that structure the entire process of data extraction, transformation, and storage using serverless Azure services to deploy models and analytical solutions for the enterprise within a specific Function.
It is essential that the Chapter Lead- Data Engineer can manage quality assurance, data migration and integration, and solution deployment to ensure the business gets the best value. This will be achieved by building strong relationships and collaboration with members of the broader HEINEKEN data organisation as well as various programs across the central, regional and Operating Company (OpCo) structures.
In particular, Chapter Lead will partner with a growing group of data professionals such as Data Scientists, Machine Learning Engineers and Product Managers who play a crucial role in the development and delivery of Analytics products at scale.
Your responsibilities would include:
structuring end-to-end processes of data extraction, transformation, and storage to deploy models and analytical solutions in real-time and offline analytic processing
handling activities such as quality assurance, data migration and integration, and solution deployment to ensure the business gets the best value
implementing, maintaining, and further developing ETL processes, data lineage, and observability across large-scale data ingestion from a variety of sources
designing and implementing data flows to ensure efficient and reliable data movement (e.g. unit and integration tests)
providing technical support in understanding business problems and designing smart data products
collaborating within an agile culture, contributing to the team's success
maintaining strong relationships with stakeholders to ensure collaboration and delivery of objectives (relationship creation and management of broader team’s stakeholders to ensure strong connection and collaboration for team)
continuing self-development and researching best-in-class analytical approaches (management and/or development and capability building of Junior/Senior Data Engineers)
leading the chapter.
You are a good candidate if you have:
MSc/PhD in statistics, mathematics, or a related field
5+ years in a pure analytical/science role
3+ years of management experience (management / leadership of related domain experts)proven experience in executive communications
experience setting team vision and strategy
significant commercial experience in a similar position
proficiency with Python (inc. strong data analytics skills using Python)
excellent software engineering skills (including unit testing, integration testing, OOP)
experience working with large datasets through Spark and RDBMS
solid knowledge of PySpark with the ability to apply it to write Spark applications as well as analyze data in a distributed environment
experience working with a large development team (CI/CD)
very good SQL skills and ability to extract information from databases
ability to build and maintain strong collaborative relationships with stakeholders across the business
demonstrated ability to effectively manage multiple simultaneous projects and deliverables
communicate effectively with various stakeholders, tailoring your message to your audience's level of technical understanding
excellent written and verbal English.
You are a perfect candidate if you have:
experience with Azure development environment
experience in building/releasing Infrastructure as Code (e.g. Terraform)
experience with containerization technologies and orchestrators (e.g. Docker and Kubernetes)
understanding of machine learning models, deployment, and monitoring
interest in machine learning and/or desire to develop skills.
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