Sr. Product Manager- Data Warehouse (Remote)

The Sr. Product Manager, Data Warehouse will report to the Sr. Director, Data Science & Analytics in the Data Science & Analytics organization. This role will lead the product strategy and execution for our enterprise data warehouse capabilities on Snowflake—enabling trusted, governed, and performant analytics data for business intelligence, reporting, self-service exploration, and AI/ML applications. You will be a trusted partner to data engineering, architecture, security, governance, and business stakeholders to deliver measurable value through improved data quality, usability, reliability, and time-to-insight.

 

You will own the product vision and roadmap for core warehouse capabilities in Snowflake, including data modeling (dimensional/data vault where appropriate), semantic and metrics layers, Generative AI features, workload performance and SLAs, governed data access, lineage and observability, and enablement for BI and analytics tooling. This is a highly cross-functional role requiring strong product leadership, understanding of the business meaning of the data, deep fluency in modern data warehousing, and a robust understanding of Generative AI.

 

Duties & Responsibilities:

· Own the product vision and roadmap for the enterprise data warehouse on Snowflake to enable trusted analytics at scale.

· Partner with business stakeholders, analytics, and data engineering to translate reporting and decisioning needs into clear product requirements, data contracts, and prioritized warehouse initiatives.

· Develop and execute product roadmaps with measurable outcomes (OKRs/KPIs) such as time-to-data, query performance, data quality, adoption, and cost efficiency.

· Define the warehouse product strategy across ingestion, transformation, modeling, serving, and consumption layers; balance short-term delivery with long-term architecture and platform evolution.

· Partner with Data Science and Data Engineering to develop and execute on a roadmap for applications that use Snowflake’s Generative AI features.

· Collaborate with Architecture, Security, Privacy, and Data Governance to ensure the warehouse meets governance, access control, retention, audit, and compliance requirements.

· Establish and communicate warehouse SLAs/SLOs (freshness, availability, performance) and lead incident review/continuous improvement with engineering partners.

· Drive a 1–3 year capability roadmap (e.g., semantic layer/metrics store, self-service data products, workload isolation, data observability, catalog/lineage) and deliver iteratively.

· Prioritize features and investments using customer feedback, analytics usage telemetry, technical feasibility, risk, and business impact.

· Develop business cases for data warehouse initiatives (value, risk reduction, productivity, scalability) and track outcomes against OKRs and KPIs.

· Define and maintain product and platform dashboards (adoption, performance, freshness, quality, cost) and provide regular updates to stakeholders.

· Provide guidance and mentorship to product managers and analysts; set standards for warehouse product discovery, delivery, and stakeholder communication.

· Identify opportunities to improve scalability, reliability, latency, and cost efficiency of Snowflake workloads through workload management (virtual warehouses, resource monitoring), query optimization, and FinOps practices.

· Partner with engineering to deliver robust warehouse capabilities (modeling patterns, semantic layer, query optimization, data observability, CI/CD for data, and environment management).

· Operate effectively with minimal direction; navigate ambiguity and shifting priorities while maintaining clear delivery plans and stakeholder alignment.

· Other duties as assigned.

Qualifications

Education & Experience:

Minimum required:

· 7+ years of experience in product management required with significant ownership of platform, infrastructure, or data products

· Bachelors Degree in Computer Science, Mathematics, Statistics, Engineering or equivalent combination of education, experience and training required

· Strong understanding of data warehouse concepts: dimensional modeling, semantic/metric layers, ETL (Informatica, Talend, Matillion), orchestration, data quality, lineage, and workload performance.

· Product management experience with Generative AI applications and a robust understanding of prompt engineering, text-to-SQL, RAG, evaluation, and observability.

Additional preferred:

· 5 years of experience in Snowflake preferred

· Experience with relational data sources (SQL Server), non relational (Mongo DB), structured and unstructured data sources

· Masters Degree in Computer Science, Mathematics, Statistics, Engineering preferred

· Certified Product Management credentials preferred

 

 

Skills & Abilities:

· Experience partnering with data engineering and analytics teams to deliver Snowflake-based warehouse platforms and curated data products

· Understanding of modern platform and technology solutions

· Excellent analytical skills with a strong bias towards action and a proactive nature

· Demonstrated ability to read schemas, define data contracts, and perform technical user acceptance testing

· Strong SQL skills

· Demonstrated experience with change data capture (Fivetran, Qlik Replicate, Debezium)

· Demonstrated experience in Agile and experience with Agile tools (Azure DevOps, Jira)

· Strong organizational skills with a drive to meet deadlines.

· Proven leadership skills to gain credibility, garner respect, and guide the creation of self-organizing teams

· An affinity for accuracy and efficiency

· Fluency with analytics/BI and data ecosystem concepts (e.g., BI semantic models, data catalogs, orchestration, observability); tool-specific experience is a plus

· Strong verbal and written communication skills

· An aptitude for data-driven prioritization and multi-tasking

· Seeks to understand the data that can drive business outcomes

· Strong collaboration and communication skills. Able to cultivate relationships with clients, partners, and other departments to facilitate collaboration and achieve common goals.

· A drive to learn and apply new concepts quickly.