Job Purpose:
The role in as part of the APAC Data & Analytics 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.
The role holder 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 (or a group of Functions).
It is essential that the role holder 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, he/she 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.
Key Responsibilities:
All Levels (scope and complexity will increase from single product and domain to multiple products and/or domains):
Budget responsibilities: Potential responsibility for selection of AA Vendors and AA Tooling workbench (Procurement & Enablement of tools sits with GIS).
Maintain 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).
Implement, maintain, and further develop ETL processes, data lineage, and observability across large- scale data ingestion from a variety of sources.
Handle activities such as quality assurance, data migration and integration, and solution deployment to ensure the business gets the best value.
Design and implement data flows to ensure efficient and reliable data movement (e.g., unit and integration tests).
Continued self- development and research of best- in- class analytical approached (management and/or development and capability building of Junior/Senior Data Engineers).
Collaborate within an agile culture, contributing to the team&039;s success.
Provide technical support in understanding business problems and designing smart data products.
Structure end- to- end processes of data extraction, transformation, and storage to deploy models and analytical solutions in real- time and offline analytic processing.
Qualification:
BA/MSc in Statistics, Mathematics, or a related field; equivalent work experience accepted. (MSc/PhD).
3+ years in a pure analytical/science role (5+ years).
Experience / Skills (all levels):
Ability to build and maintain strong collaborative relationships with stakeholders across the business.
Experience working with large datasets through Spark and RDBMS.
Significant commercial experience in a similar position.
Communicate effectively with various stakeholders, tailoring your message to your audience&039;s level of technical understanding.
Proficiency with Python (inc. strong data analytics skills using Python).
Excellent written and verbal communication skills.
Language: Excellent written and verbal English.
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.
Excellent software engineering skills (including unit testing, integration testing, OOP).
Demonstrated ability to effectively manage multiple simultaneous projects and deliverables.
Nice to have:
Interest in machine learning and/or desire to develop skills.
Experience with Azure development environment
Experience working in agile organizations.
Experience with containerization technologies and orchestrators (e.g., Docker and Kubernetes).
Experience in building/releasing Infrastructure as Code (e.g., Terraform)
Understanding of machine learning models, deployment, and monitoring.
Leadership competencies:
Management / leadership of related domain experts
3+ years of management experience
Proven experience in executive communications
Experience setting team vision and strategy
