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Product Manager Data Platform, Analytics & Cloud (Google Cloud Platform)

We are seeking an experienced Product Manager to own and drive a cloud-native data platform spanning databases, ETL/ELT pipelines, streaming, analytics, and reporting. This role will work closely with onshore architects, data engineering leads, analytics teams, and offshore delivery teams to define product vision, roadmap, and execution for enterprise-scale data solutions on Google Cloud Platform.

The Product Manager will bridge business requirements and technical implementation, ensuring scalable, reliable, and analytics-ready data products using Snowflake, DOMO, and Google Cloud Platform-native services.

Key Responsibilities

• Product Strategy & Roadmap
• Define and own the product vision and roadmap for the cloud data platform, analytics, and reporting ecosystem.
• Translate business objectives into clear product requirements, epics, and user stories for data engineering and analytics teams.
• Prioritize features and enhancements across data ingestion, ETL/ELT, databases, streaming, and BI layers.
• Data Platform & Analytics Ownership
• Own end-to-end data product lifecycle across:
• Operational databases (MySQL, PostgreSQL)
• Cloud databases (Spanner, Cloud SQL, AlloyDB)
• Analytics platforms (Snowflake, BigQuery)
• BI & reporting tools (DOMO)
• Ensure data products are analytics-ready, scalable, and aligned with reporting and decision-making needs.
• Drive adoption of config-driven ETL/ELT pipelines and standardized data models.
• Stakeholder Collaboration
• Partner with onshore solution architects and technical leads to align product goals with architecture decisions.
• Act as the primary interface between business stakeholders, engineering, analytics, and offshore teams.
• Gather feedback from users and stakeholders to continuously refine data products and dashboards.
• Delivery & Execution
• Work closely with engineering teams to ensure timely and high-quality delivery of data pipelines, schemas, and reports.
• Support schema evolution, data migrations, and onboarding of new data sources from a product standpoint.
• Ensure readiness for batch and near-real-time data use cases.
• Governance, Quality & Operations
• Define success metrics (KPIs) for data platform reliability, performance, and analytics adoption.
• Ensure compliance with data governance, security, and quality standards.
• Oversee documentation including product specs, data catalogs, and reporting definitions.
• Leadership & Enablement
• Guide offshore teams by providing clear product direction, acceptance criteria, and prioritization.
• Support release planning, backlog grooming, and sprint ceremonies.
• Champion best practices for data modernization and cloud-native analytics.

Mandatory Skills & Experience

• 5-8 years of experience as a Product Manager, Business Analyst, or Product Owner in data-centric platforms.
• Strong understanding of data platforms, databases, ETL/ELT, and analytics ecosystems.
• Hands-on exposure to Snowflake for analytics and DOMO for reporting and dashboards.
• Experience working with cloud data platforms on Google Cloud Platform, including BigQuery, Pub/Sub, Dataflow, and Cloud Storage.
• Ability to translate complex technical concepts into business-friendly product requirements.
• Experience working with distributed/onshore-offshore teams.
• Strong communication, stakeholder management, and prioritization skills.
• Exposure on multi country data would be good

Nice to Have

• Exposure to enterprise databases and technologies such as AS/400, MongoDB, Cassandra, or GraphQL.
• Experience in enterprise data modernization or legacy-to-cloud transformation programs.
• Familiarity with CI/CD concepts for data pipelines and analytics deployments.

What Success Looks Like

• A clearly defined and executed data platform roadmap aligned with business goals.
• High adoption of Snowflake-powered analytics and DOMO dashboards by business users.
• Scalable, reliable data products enabling faster insights and decision-making.
• Strong collaboration between business, engineering, and analytics teams.