Data COE-Technical Product Owner

1 day ago

Mumbai, Maharashtra, India Mondelez Full time ₹ 12,00,000 - ₹ 24,00,000 per year

About the Role

The Data COE Technical Product Owner will be part of Technology Enablement team and would be responsible for defining and implementing best practices, frameworks, and tools that support scalable data ingestion and engineering processes.

This includes building robust backend services and intuitive front-end interfaces to enable self-service, observability, and governance in data pipelines across the enterprise.

Key Responsibilities:

  • Lead the development of reusable software components, libraries, and frameworks for data ingestion, transformation, and orchestration.
  • Design and implement intuitive user interfaces (dashboards, developer portals, workflow managers) using and modern frontend technologies.
  • Develop backend APIs and services to support data engineering tools and platforms.
  • Define and enforce software engineering standards and practices across the Data COE for developing and maintaining data product.
  • Collaborate closely with data engineers, platform engineers, and other COE leads to gather requirements and build fit-for-purpose engineering tools.
  • Integrate observability and monitoring features into data pipeline tooling.
  • Lead evaluations and implementations of tools to support continuous integration, testing, deployment, and performance monitoring.
  • Mentor and support engineering teams in using the frameworks and tools developed.

Qualifications:

  • Bachelors or masters degree in computer science, Engineering, or related discipline.
  • 10+ years of data engineering experience, with at least 5 years in software engineering, platform, or infrastructure roles.
  • 3+ years of cloud experience on Google Cloud Platform.
  • Backend development experience in Python with exposure to microservices architecture FAST APIs and RESTful APIs.
  • Experience working with data engineering tools such as Apache Airflow, Kafka, Spark, Delta Lake, and DBT.
  • Familiarity with GCP cloud platforms, containerization (Docker, Kubernetes), and DevOps practices.
  • Strong understanding of CI/CD pipelines, testing frameworks, and software observability.
  • Ability to work cross-functionally and influence without direct authority.

Preferred Skills:

  • Proven experience with building internal development platforms or self-service portals.
  • Familiarity with data catalogue, metadata, and lineage tools (e.g., Collibra).
  • Familiarity with Data Quality rules and tools like Ataccama, Data observability tools like Datadog.
  • Understanding of data governance and data mesh concepts.
  • Agile delivery mindset with strong emphasis on automation and reusability.

Tools and Technologies

  • Frontend Development:
  • Backend Development: Python, FAST APIs, RESTful APIs, Microservices Architecture
  • Cloud Platform: GCP
  • Data warehousing tech: Big Query
  • Containerization: Docker, Kubernetes
  • CI/CD & DevOps: CI/CD pipelines, Testing Frameworks, Software Observability
  • Data Governance: Data catalogue tools (e.g., Collibra), Metadata Management, Lineage Tools (Collibra), Data Quality tools (Ataccama), Data Observability tools (Datadog), Data Mesh concepts.
  • Data Engineering Tools: DBT, Apache Airflow, databricks

Why Join Us?

  • Play a strategic role in developing the data engineering backbone for a next-generation enterprise Data COE.
  • Work with cutting-edge data and software technologies in a highly collaborative and innovative environment.
  • Drive meaningful change and enable data-driven decision-making across the business.

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