Digital & Technology Team (D&T) is an integral division of HEINEKEN Global Shared Services Center, committed to making Heineken the most connected brewery through digitalized and integrated processes, best-in-class technology, and a data-driven culture.
As Senior Data Engineer in the Data Foundation scope, you will act as a technical expert responsible for configuring, developing, and integrating products and platforms across operating companies. You will provide guidance aligned with architecture and business objectives, drive platform operations within service-level agreements, and collaborate with cross-functional teams to deliver efficient development pipelines.
The role reports directly to the Data Engineering Lead.
Responsibilities
- Coach and mentor Data Engineers in designing, developing, and delivering scalable, reliable, high-performing big data solutions.
- Design, develop, and maintain scalable data pipelines and ETL processes.
- Monitor and optimize data infrastructure performance, resolving bottlenecks and issues.
- Contribute as an individual engineer for approximately 60% of the role.
- Ensure adherence to coding standards, best practices, and architectural guidelines.
- Oversee technical architecture implementation and resolve technical challenges.
- Ensure DevSecOps practices are embedded in daily team activities.
- Coordinate software development, address technical debt, and support onboarding and talent development.
- Lead technical discussions with other teams and represent the domain in broader cross-functional discussions.
- Improve processes that enhance engineering efficiency and quality.
- Align project and sprint goals, timelines, and resource allocation with the Engineering Manager, Product Owner, and Scrum Master.
Requirements
- 8+ years of experience in Data Engineering.
- Strong understanding of data integration, ETL processes, and data warehousing.
- Proficiency in Python and SQL, with experience in MPP and streaming technologies.
- Experience with cloud platforms such as AWS, Azure, or GCP and data solutions including Databricks, BigQuery, or Snowflake.
- Experience with CI/CD tools including Azure DevOps, Jenkins, and Git.
- Experience with APIs, PySpark, Azure Data Factory, Azure Synapse, Databricks, Microsoft Fabric, Power BI, and Apache Kafka or similar technologies.
- Knowledge of data modelling, architecture, governance, compliance, software development principles, and modern architecture.
- End-to-end DataOps or Data Engineering project experience.
- Proven ability to lead engineering teams, mentor team members, make critical technical decisions, and collaborate with technical and non-technical stakeholders.
Nice to have
- Experience with logging and monitoring using Azure or Databricks services.
- Experience with machine learning and AI technologies.
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