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Data Engineering Lead

Summary

Lead a team of data engineers to build and maintain scalable Azure-based data pipelines and ETL processes using Databricks, PySpark, and SQL, while mentoring engineers and driving DataOps best practices.

Digital & Technology Team (D&T)

Heineken Global Shared Services Center’s D&T is committed to making Heineken the most connected brewery. We digitalize and integrate our processes, ensure best-in-class technology, and embed a data‑driven culture. Join us and have a direct impact on building the future of Heineken.

Responsibilities

  • Lead a team of experienced data engineers in designing, developing, and delivering scalable, reliable, and high‑performing software solutions.
  • Lead the design, development, and maintenance of scalable data pipelines and ETL processes.
  • Monitor and optimize data infrastructure performance, identifying and resolving bottlenecks and issues.
  • Drive operational excellence including code reviews, design reviews, testing, and deployment processes.
  • Act as an individual contributor (~60%) engineering the software products/solutions alongside the team.
  • Ensure the team adheres to coding standards, best practices, and architectural guidelines.
  • Oversee the implementation of the technical architecture and solve immediate technical challenges.
  • Implement good practices, coding standards, and modern architecture for DataOps; be the go‑to person for technical decisions and problem solving within the team.
  • Ensure execution of DataOps is embedded in the team’s daily work.
  • Inspire, advise, and drive the selection of development approaches.
  • Coordinate software development and address technical debt within the team.
  • Hire, onboard, mentor and develop top engineering talents, fostering a culture of learning.
  • Guide and mentor team members, fostering their professional and personal growth.
  • Build career paths and incentive structures for teams, empowering members to achieve them.
  • Grow new generations of talents and future leaders.
  • Drive collaboration and continuous improvement.
  • Lead technical discussions with other teams/departments and oversee the state‑of‑the‑art quality of the stack.
  • Represent the domain in broader technical discussions across domains.
  • Design and improve processes that enhance efficiency and quality.
  • Communicate with Engineering Manager, Product Owner, Business Analyst, and Scrum Master to align on project or sprint goals, timelines and resource allocation.

Qualifications

  • 8+ years of experience in data engineering or software engineering.
  • 5+ years of managerial experience.
  • Hands‑on experience and in-depth knowledge of:
    • Azure cloud data services & technologies
    • Azure Databricks, Unity Catalog, Delta Live Tables
    • Data modelling and architecture
    • ETL pipeline design; expert in Python, PySpark, and SQL
    • Azure Data Factory
    • Azure DevOps
    • Logging and monitoring using Azure/Databricks services
    • Apache Kafka
    • Databricks online tables
    • Synapse, Fabric, Power BI, Azure Functions, Azure Logic Apps
    • Jira
  • Strong understanding and implementation of software development principles, coding standards, and modern architecture.
  • Hands‑on experience in implementing and managing end‑to‑end DataOps/Data Engineering projects in a team.
  • Proven ability to lead software development teams of engineers of varying experience, adapting to team sizes from small to large.
  • Experience working on diverse projects with varying technologies, products, and systems.
  • Strong problem‑solving skills and ability to make critical technical decisions.
  • Ability to guide and mentor other team members.
  • Successful people‑managerial experience.
  • Pragmatic and collaborative approach.
  • Experience with Databricks, data pipelines, CI/CD.
  • Proficiency in Python, SQL and big data technologies in cloud environment.

Nice to Have

  • Knowledge of GCP and AWS cloud services.
  • Shell scripting / Azure CLI knowledge.

See also