Product Manager

AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics.
Do You Dream Big?
We Need You.
Job Description
Job Title: Product Manager
Location: Bangalore
PURPOSE OF ROLE
BrewDat is ABI’s data platform, powering data products and AI solutions across all our domains – from sales and marketing to supply, finance, people, and more.
We provide the data foundations, frameworks, and tools that enable teams across ABI to ingest, transform, govern, and serve data at scale - following Data Mesh and Domain-Driven Design principles.
About the Role
We’re looking for a Product Manager with a strong technical background to lead the Integration products of BrewDat.
Your main mission is to:
Build and evolve the vision, strategy, and roadmap for BrewDat’s data engineering capabilities (ingestion, transformation, and serving).
Understand and prioritize user needs from data engineers, analytics engineers, ML engineers, and domain teams.
Turn complex platform capabilities into clear, usable products that make data teams more productive and autonomous.
Build our Integration-as-a-Service platform and guide the transition from legacy middleware to cloud-native architectures
You’ll work in a cross-functional squad alongside engineers, a Delivery Manager, architects, and governance specialists, and you’ll collaborate closely with the Adoption team, who bring users’ needs to the product area.
KEY TASKS AND ACCOUNTABILITIES
Product Strategy & Vision
Define and evolve the product vision for BrewDat's data engineering layer (ingestion, transformation, and serving).
Translate company and data strategy into a clear, prioritized roadmap for your squad.
Discovery & User-Centricity
Deeply understand the needs of data engineers, analytics engineers, domain squads, and internal platform users.
Run product discovery: interviews, usage analysis, experiments, and feedback loops with internal customers.
Roadmap & Delivery
Own and manage the product backlog for the Data Engineering squad.
Write clear problem statements, user stories, and acceptance criteria, focusing on outcomes rather than outputs.
Work in an Agile environment, participating in ceremonies and ensuring alignment between Product, Engineering, and Architecture.
Measurement & Continuous Improvement
Define and track product KPIs: adoption, CSAT from users, build times, time-to-data, platform reliability, etc.
Use data and feedback to continuously refine priorities and validate if shipped features are creating value.
Promote a culture of experimentation and continuous improvement within the squad.
Stakeholder Management & Communication
Align with multiple stakeholders (domains like sales, marketing, supply, finance, tech, etc.).
Communicate roadmap, progress, trade-offs, and impact clearly and frequently.
Partner with the Adoption team to launch new capabilities, manage change, and scale usage.
Middleware
Managing the consolidated middleware roadmap, prioritizing global reliability frameworks (like cross-zone replication/caching), and tracking integration unit economics (e.g., standardizing integration cost per application).
QUALIFICATIONS, EXPERIENCE, SKILLS:
Must-Have
Solid experience as a Product Manager (or Product Owner acting as PM) in:
Data platforms, data engineering, analytics platforms, or developer/platform tools, or
Technical products with strong infrastructure or backend components.
Technical background (e.g., Computer Science, Engineering, Data, or equivalent experience). You don't need to code daily, but you must:
Be comfortable discussing architecture, pipelines, and technical trade-offs with engineers.
Understand concepts like data pipelines, ETL/ELT, orchestration, data lakes, data warehouses, and APIs.
Broaden the technical scope to include API management, event-driven architectures, and microservices alongside the existing data pipeline concepts.
Strong skills in:
Product discovery and problem framing.
Prioritization and roadmap management.
Ability to navigate complex stakeholder environments, negotiate priorities, and align diverse interests.
Strong communication skills in English (written and spoken).
Nice-to-Have (Differentials)
Experience with some of the technologies and concepts we use is a big plus, but not mandatory:
Cloud & Data: Azure, Databricks, Apache Spark, Airflow, Unity Catalog.
Engineering Practices: GitHub, CI/CD, code review flows, Data Mesh.
Experience with internal platforms or "products for developers/data teams" is especially valuable.
Explicitly call out experience with legacy-to-cloud migrations (e.g., MuleSoft to Camel-K), Azure DevOps for delivery tracking, and deep observability tools like Datadog.
And above all of this, an undying love for beer!
We dream big to create future with more cheers

Work arrangement
No