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Product
·
San Francisco Bay Area, CA
·
Hybrid
Sr. Product Manager
APPLY
Job SummaryPantomath is hiring a Senior Product Manager for Connectors with direct, hands-on data engineering experience to own the strategy and execution of our integrations ecosystem.This role sits squarely at the intersection of product leadership and data engineering. You will be responsible for defining how Pantomath connects across the modern data stacks- from ingestion and transformation (Fivetran, dbt, Airflow) to cloud warehouses (Snowflake, Databricks) to analytics and BI tools (Tableau, Power BI).This is not a generalist PM role. To be successful, you must have firsthand experience designing, building, or maintaining data pipelines and integrations and be comfortable engaging deeply with technical architecture, APIs, and performance trade-offs. You will use that experience to set technical direction, write precise requirements, and partner closely with engineering to deliver reliable, scalable, production-grade connectors.What You’ll DoOwn the connectors product strategy and roadmap, making informed, technical decisions about which integrations to build.Leverage your data engineering background to evaluate feasibility and long-term maintainability of integrations.Translate customer needs, partner requirements, and technical constraints into clear, detailed PRDs that engineers can execute against without ambiguity.Partner closely with engineering to design, build, test, and ship connectors that meet strict standards for reliability, scalability, observability, and security.Replicate real-world customer data environments and pipelines to validate connector behavior, and ensure production readiness.Define success metrics for connectors (adoption, reliability, latency, error rates) and actively monitor, diagnose, and iterate based on data and feedback.Work with Go-to-Market teams to support launch readiness, technical enablement, and customer-facing documentation.Stay current on trends and best practices across ETL/ELT, APIs, orchestration, data observability, and cloud data...
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