Technical Product Manager, Data and Internal Products

Accountabilities: You will lead the strategy, prioritization, and delivery of internal technical products, ensuring that data assets and shared platforms evolve to meet the organization's growing needs. Your responsibilities will include: Own the product vision, roadmap, and execution for internal technology initiatives, particularly those involving data-intensive systems and infrastructure. Lead cross-functional projects to improve the quality, reliability, accessibility, and usability of internal datasets, platforms, and shared services. Drive long-term initiatives to modernize and future-proof internal data and technology assets, ensuring they can scale with evolving business and technical requirements. Partner with engineering, data science, solutions analytics, and product teams to understand their needs, define use cases, and translate technical challenges into actionable product requirements. Manage prioritization across competing internal demands, balancing immediate operational impact with long-term strategic value. Coordinate complex initiatives involving multiple stakeholders, ensuring clear ownership, alignment, and effective management of cross-functional dependencies. Support the development and improvement of data pipelines, data models, and internal tooling that enable reliable analytics and machine learning workflows. Monitor product performance and continuously identify opportunities to improve internal systems and technical processes. Requirements The ideal candidate combines strong product management experience with a technical background in engineering, data science, or analytics. You should have hands-on familiarity with large-scale data environments and a proven ability to lead complex internal initiatives. The following qualifications are essential: 5+ years of experience in product management, founding roles, or equivalent cross-functional product leadership positions. Demonstrated experience managing both big data products and internal tools, with specific projects clearly identified on your resume. At least one year of experience at a Series B or Series C startup; your current or most recent role must be at a startup rather than a large technology company. Previous experience in a technical role, such as Software Engineer, Data Scientist, Machine Learning Engineer, or highly technical Data Analyst. Production-level experience with data pipelines, including data ingestion, cleaning, normalization, and modeling, with specific tools and projects clearly identified. Familiarity with Python and AWS. Hands-on experience with at least one major big data technology, such as Spark, Databricks, BigQuery, Snowflake, or Redshift. Strong understanding of big data concepts, data architecture, data pipelines, and data modeling. Proven ability to collaborate with engineering, data science, and analytics teams on complex technical challenges. Experience leading large internal initiatives, coordinating multiple stakeholders, and managing cross-functional dependencies. Must be located in the United States and legally authorized to work there. Additional experience that would be advantageous: Background in fintech, payments, fraud prevention, identity verification, or related domains. Benefits Annual base salary: $180,000–$230,000 USD. Equity as part of the overall compensation package. Comprehensive benefits, including employer-paid health insurance for employees and their dependents. Fully remote, remote-first working environment for US-based employees. Flexible paid time off. Regular company-wide in-person events. Opportunity to contribute to large-scale fraud prevention and identity technology used by major financial institutions. Work in a well-funded, high-growth environment backed by established venture capital investors. Opportunity to help shape internal data infrastructure and technical products with significant organizational impact.