Product Manager-Unified Data Platform

Role Summary

We are looking for an accomplished Product Manager to define, lead, and scale our Enterprise Data Management Platform a unified foundation that powers data ingestion, transformation, storage, governance, quality, and analytics across the organization.

The ideal candidate will bring extensive experience across the data lifecycle, including data lake and warehouse architectures, data governance frameworks, and data quality management. This role demands a balance of strategic vision, technical acumen, and leadership to deliver a trusted, scalable, and insight-driven data ecosystem.

Key Responsibilities

• Define and own the vision, strategy, and roadmap for the Data Management Platform covering ingestion, transformation, storage, governance, and consumption layers.
• Lead the design and implementation of streaming and batch ingestion pipelines to collect data from diverse enterprise systems.
• Drive the creation of ETL/ELT workflows ensuring seamless data movement and transformation across platforms.
• Oversee the setup and modernization of data lakes, data warehouses, and lakehouse architectures to support both analytical and operational workloads.
• Establish and enforce data governance frameworks, including data lineage, cataloging, quality, metadata management, access control, and compliance.
• Partner with data engineering, data science teams to ensure architectural alignment with business goals.
• Implement data stewardship models across business domains to ensure data accountability and consistency.
• 
  Evaluate and onboard tools for data observability, data quality monitoring, and lifecycle management (retention, archival, and purging).
• Define and monitor KPIs for data quality, accessibility, and timeliness, ensuring continuous improvement through analytics and automation.
• Promote data democratization by enabling governed self-service access through catalogs, APIs, and visualization tools.

Required Skills & Qualifications

• 5+ years of Product Management experience in Data Platforms, Data Engineering, or Data Governance.
• Strong understanding of data architecture principles — including data modeling, ETL/ELT, and data lake/warehouse design.
• Deep knowledge of data governance, including ownership, stewardship, lineage, quality, and compliance.
• Hands-on exposure to at least one data governance or quality tool is mandatory.
• Proven experience with tools and frameworks such as:
• Data Cataloging & Metadata Management
• Data Quality & Observability
• Data Lineage & Governance

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• ETL / ELT & Integration
• Data Lakes & Warehouses
• Familiarity with data orchestration and workflow automation
• Knowledge of data security, RBAC, and compliance frameworks (GDPR, CCPA, HIPAA).
• Strong analytical, problem-solving, and stakeholder management skills with the ability to translate data capabilities into business value.

Preferred Qualifications

• Experience implementing enterprise data governance programs
• Working knowledge of data mesh or data fabric architectures.
• Experience with real-time data streaming (Kafka, Spark Structured Streaming, Flink).
• Familiarity with schema evolution and data versioning concepts.
• Exposure to business intelligence platforms for self-service analytics.
• Experience managing machine learning data pipelines and feature stores .