Product Owner

Product Owner Data Engineering

Location: Bangalore, India (Hybrid)
Experience: 6+ Years

About the Role

We are looking for an experienced Product Owner Data Engineering to drive data engineering products and solutions across enterprise data platforms. The role requires a strong combination of Product Ownership, SQL, Data Engineering, Data Quality, and stakeholder management skills.

The ideal candidate will act as the bridge between business stakeholders and technical teams, translating business requirements into actionable user stories, data requirements, acceptance criteria, and prioritized product roadmaps.

Key Responsibilities

Product Ownership & Roadmap Management

Own and prioritize the Data Engineering product backlog based on business value, risk, dependencies, and technical feasibility.
Define product objectives, roadmap, milestones, acceptance criteria, and success measures.
Manage backlog refinement, prioritization, sprint planning, demos, and release activities.

Business Requirement Translation

Partner with business stakeholders, SMEs, Data Owners, Data Stewards, IT teams, and engineering teams to understand business needs.
Translate business requirements and data-quality rules into user stories, technical requirements, data rules, and acceptance criteria.
Conduct requirement workshops and ensure clear alignment between business and technical teams.

Data Analysis & Validation

Perform hands-on SQL analysis to understand datasets, investigate data-quality issues, validate engineering outputs, and support root-cause analysis.
Define and validate data-quality controls covering completeness, consistency, reconciliation, duplicates, exceptions, outliers, and business rules.
Analyze source-to-target data and validate transformation logic.

Data Engineering Collaboration

Work closely with Data Engineers to deliver reliable data pipelines, curated datasets, data-quality solutions, and analytical data products.
Participate in technical discussions involving Databricks, PySpark, SQL, data transformations, data models, source-to-target mappings, and pipeline dependencies.
Understand ETL/ELT processes, data warehouses/lakehouses, and modern data engineering architectures.

Stakeholder & Cross-Functional Management

Act as the primary bridge between business stakeholders and technical teams.
Communicate technical concepts, limitations, risks, dependencies, and trade-offs in business-friendly language.
Coordinate with cross-functional teams to resolve issues and ensure timely delivery.

Data Quality & Governance

Establish data-quality requirements, validation rules, exception-management processes, and remediation workflows.
Collaborate with Data Owners and Data Stewards to establish data accountability and appropriate review and approval processes.
Drive continuous improvement in data quality and governance practices.

Business Domain & Value Alignment

Understand data requirements across Supply Chain, Finance, procurement, inventory, demand planning, product/master data, and ERP operations.
Ensure product priorities are aligned with measurable business outcomes such as:
Inventory and planning accuracy
Operational efficiency
Data-quality improvement
Process optimization
Cost savings

Testing, Release & Adoption

Define acceptance criteria and coordinate business/UAT validation.
Validate datasets and data products against functional and business requirements before release.
Monitor adoption, data quality, and business outcomes after implementation.

Must-Have Skills & Experience

Strong SQL skills, including complex joins, CTEs, aggregations, window functions, reconciliation, exception identification, and data-quality analysis.
Strong understanding of Data Engineering concepts, including ETL/ELT, data pipelines, data transformations, data models, data warehouses/lakehouses, and source-to-target mappings.
Working knowledge of Databricks and PySpark; ability to understand PySpark notebooks and transformation logic and effectively collaborate with Data Engineers.
Proven Product Owner / Agile experience, including backlog management, user stories, acceptance criteria, prioritization, and Agile delivery.
Excellent stakeholder management and communication skills with the ability to translate business requirements into technical deliverables.
Experience working with business SMEs, technical teams, leadership, Data Owners, and Data Stewards.

Good-to-Have Skills

Hands-on experience with Snowflake or Azure Data Engineering.
Knowledge of SQL and NoSQL databases such as PostgreSQL, MySQL, MongoDB, or Cassandra.
Experience with ERP and Master Data Management.
Data visualization experience with Power BI or Tableau.
Relevant cloud/data engineering certifications.
Basic understanding of Machine Learning and Generative AI concepts.
Experience in Supply Chain, Finance, procurement, inventory, or related business domains.

Key Skills

Product Owner | Data Engineering | SQL | Databricks | PySpark | ETL/ELT | Data Quality | Data Governance | Agile | User Stories | Backlog Management | Stakeholder Management | Data Warehousing | Source-to-Target Mapping | Supply Chain Data