Data Product Manager

Role: Data Product Manager
Location: Bay Area, CA/Remote

Job Summary:

• Own and manage data product initiatives in partnership with Data Engineering, Analytics, Cloud, and business stakeholders.
• Develop a strong understanding of data models, data pipelines, data warehouses, data lakes, and analytics environments.
• Partner with engineering teams to define and deliver data products leveraging Snowflake, Databricks, and AWS cloud services.
• Gather business requirements and translate them into clear product requirements, user stories, acceptance criteria, and functional specifications.
• Define and maintain the data product roadmap, prioritizing features based on business value, customer impact, technical dependencies, and organizational priorities.
• Work with Data Engineering teams on Snowflake data warehouse, Databricks Lakehouse, ETL/ELT pipelines, data ingestion, transformation, and data integration initiatives.
• Collaborate with AWS teams on cloud-based data solutions using services such as S3, Glue, Lambda, Redshift, and AWS data integration services.
• Partner with technical teams to understand Snowflake architecture, data models, SQL workloads, data sharing, performance, and data governance requirements.
• Work with Databricks teams on Delta Lake, data pipelines, notebooks, workflows, Spark-based processing, and Lakehouse architecture.
• Use Linear, Jira, or similar project management tools for sprint planning, backlog management, prioritization, and delivery tracking.
• Build and maintain project plans, track milestones, risks, dependencies, issues, and delivery timelines.
• Coordinate with cross-functional stakeholders to drive execution and communicate product status, risks, decisions, and delivery updates.
• Oversee dashboard maintenance and enhancements to ensure data accuracy, reporting consistency, performance, and alignment with business requirements.
• Define and monitor data product KPIs, adoption metrics, quality metrics, and business outcomes.
• Collaborate with Data Engineering and Data Governance teams to establish data quality, lineage, security, privacy, and governance standards.
• Identify opportunities to improve existing data products through automation, self-service analytics, improved data quality, and scalable cloud architecture.
• Support end-to-end delivery of data products from discovery and requirements through development, testing, deployment, adoption, and continuous improvement.
• Facilitate communication between technical and non-technical stakeholders and translate complex data concepts into clear business outcomes.

Required Skills & Qualifications

• 5+ years of experience in Product Management, Data Product Management, Technical Product Management, or Data/Analytics Program Management.
• Strong understanding of data engineering, data warehousing, data lakes, ETL/ELT, data pipelines, and analytics platforms.
• Hands-on product experience working with Snowflake, Databricks, and AWS data technologies.
• Strong understanding of Snowflake data warehouse concepts, SQL, data modeling, performance, and data integration.
• Experience working with Databricks Lakehouse, Delta Lake, Spark, workflows, and data engineering pipelines.
• Understanding of AWS cloud architecture and data services, particularly S3, Glue, Lambda, Redshift, and related analytics services.
• Strong experience with Agile/Scrum methodologies, sprint planning, backlog management, and product delivery.
• Experience using Jira, Linear, Confluence, or similar product/project management tools.
• Strong analytical, problem-solving, communication, and stakeholder-management skills.
• Ability to work effectively with Data Engineers, Data Architects, BI Developers, Analysts, Cloud Engineers, and business stakeholders.
• Experience defining product roadmaps, user stories, acceptance criteria, KPIs, and success metrics.