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.