Product Manager – Data Engineering Integration

About the role

AB InBev GCC is looking for a Product Manager to lead the Integration products of BrewDat, the company’s data platform that powers analytics and AI across sales, marketing, supply, finance and more. You will shape the vision, strategy and roadmap for data engineering capabilities such as ingestion, transformation and serving, helping internal data teams become more productive and autonomous.

Key responsibilities

• Define and evolve the product vision and roadmap for BrewDat’s data engineering layer, translating company strategy into actionable plans.
• Conduct product discovery with data engineers, analytics engineers, ML engineers and domain squads to capture needs and validate solutions.
• Own the product backlog, write clear problem statements, user stories and acceptance criteria, and work in an Agile environment with engineers, architects and governance specialists.
• Define and track KPIs (adoption, CSAT, build times, platform reliability) and use data to continuously refine priorities.
• Manage the consolidated middleware roadmap, prioritising reliability frameworks and integration cost economics.
• Communicate roadmap, progress and trade‑offs to multiple stakeholders across sales, marketing, supply, finance and technology.

Required profile

• Proven experience as a Product Manager (or Product Owner) on data platforms, data engineering or developer‑focused tools.
• Technical background (Computer Science, Engineering or equivalent) with the ability to discuss architecture, pipelines and technical trade‑offs.
• Strong product discovery, prioritisation and roadmap management skills.
• Excellent communication in English and ability to navigate complex stakeholder environments.

Required skills

• Data platform concepts: data pipelines, ETL/ELT, orchestration, data lakes, data warehouses, APIs.
• API management, event‑driven architectures, microservices.
• Cloud & data technologies: Azure, Databricks, Apache Spark, Airflow, Unity Catalog.
• Engineering practices: GitHub, CI/CD, Data Mesh.
• Legacy‑to‑cloud migration tools: MuleSoft, Camel‑K, Azure DevOps.
• Observability tools: Datadog.