Principal Product Manager (Data and Integrations)
New
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SOVRAPublic procurement software
Location: United States—RemoteFull-TimePrincipal
Salary not disclosed
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Job Details
- Required Skills
- Business IntelligenceETLSnowflakeRESTful APIsBigQueryDatabricks
Requirements
- Have significant experience as a technical product manager or product lead.
- Translate technical concepts into clear business value and align stakeholders across engineering, go-to-market, and leadership.
- Have built and shipped client-facing embedded analytics and BI within a product, delivering measurable customer value beyond access to data.
- Have experience with platforms such as MSFT BI, AWS QuickSuite, or Tableau Embedded.
- Have worked with data lake architectures and modern cloud data platforms such as Snowflake, Databricks, BigQuery, or Delta Lake.
- Have experience with data modeling, pipeline orchestration, and governance best practices.
- Have delivered offerings that address government compliance and security concerns such as SOC2, FEDRAMP, or FISMA.
- Have owned APIs, integrations, data platforms, or internal infrastructure products.
- Have hands-on knowledge of RESTful APIs, webhooks, ETL processes, data synchronization strategies, and API security best practices.
- Hold a bachelor’s degree or have equivalent hands-on experience.
Responsibilities
- Lead vision, strategy, delivery, and go-to-market for customer-facing data analytics and integrations offerings.
- Bring embedded and self-service reporting into the product, including packaging and pricing.
- Work with engineering, security, and compliance teams to design APIs, integration frameworks, and synchronization patterns for real-time and batch use cases.
- Set success metrics, track performance and adoption, and guide platform investment using that evidence.
- Own the vision, architecture, and roadmap for the feature’s Datalake, including governance standards, pipeline strategy, and access patterns.
- Lead decisions on data accuracy, consistency, and reliability across systems, including schemas and synchronization approaches at scale.
- Build the data foundation for AI capabilities, including agency similarity, comparable solicitations, and outcome tracking.
- Partner with government agencies, partners, and product teams to understand needs and prioritize work.
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