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SentiLink

Technical Product Manager, Data and Internal Products

Reposted Yesterday
Remote
Hiring Remotely in United States
Senior level
Remote
Hiring Remotely in United States
Senior level
The Product Manager will lead internal tech initiatives, focusing on data-heavy systems and datasets, ensuring scalability and alignment across teams.
The summary above was generated by AI

SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transaction with confidence. We’re building the future of identity verification in the United States replacing a clunky, ineffective, and expensive status quo with solutions that are 10x faster, smarter, and more accurate.

We’ve seen tremendous traction and are growing extremely quickly. Our real-time APIs have helped verify hundreds of millions of identities, starting with financial services and rapidly expanding into new markets. SentiLink is backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.

We’ve earned recognition from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, American Banker, LendIt, and have been named to the Forbes Fintech 50 list every year since 2023. Last but not least, we’ve even made history - we were the first company to go live with the eCBSV and testified before the United States House of Representatives on the future of identity.

SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We operate as a digital-first company with strong collaboration across the U.S. and India. We maintain physical offices in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India. If you’re located near one of these offices, we would love for you to spend time in the office regularly. Some roles are hybrid or in-office by design. For example, our engineering team in India works primarily from our Gurugram office.

Role

We’re looking for a Product Manager with a technical background to lead internal initiatives within SentiLink’s Tech organization. This team builds and maintains SentiLink’s core internal technology, spanning critical datasets, internal services, and the underlying platforms that support our products and analytics. Many of these systems are data-heavy and highly interdependent, requiring strong product stewardship to ensure clarity, quality, and coordinated execution.

While the portfolio will include a range of internal technical projects, many of the most impactful initiatives are deeply data-driven. You will work on efforts that improve how we acquire, structure, and operationalize data across the company—building internal assets that support both current product lines and future innovation. You will bring product discipline and project leadership to work that spans engineering, data science, solutions analytics, and product teams.

In this role, you will partner with teams across the company to understand how internal systems and datasets are used today and what they must support as we scale. You will translate varied internal needs into clear product requirements, prioritize improvements, and drive delivery from concept through adoption.

Responsibilities

  • Own the product vision, roadmap, and execution for internal technical initiatives, with a strong focus on data‐intensive systems and foundational datasets.

  • Lead cross-functional efforts to improve the quality, reliability, and usability of internal systems, including datasets, shared services, and internal platforms.

  • Drive long-term initiatives to future-proof internal data and technology assets, ensuring they scale with evolving product, analytics, and operational needs.

  • Partner with engineering, data science, solutions analytics, and product stakeholders to understand use cases, clarify requirements, and identify interdependencies.

  • Manage prioritization across competing internal demands, balancing immediate impact with long-term strategic value.

  • Translate complex internal needs into clear, actionable specifications and ensure alignment across teams.

  • Apply structured project management to initiatives with multiple teams, ambiguous problem spaces, and intricate technical dependencies.

  • Define and track success metrics for internal systems and datasets, such as quality, completeness, latency, reliability, and stakeholder satisfaction.

  • Communicate roadmap, progress, risks, and tradeoffs to internal stakeholders at all levels.

Requirements

  • 5+ years of experience with data-heavy or platform-oriented products, with a focus on ML/Data Science strongly preferred.

  • Hands-on experience working with large datasets, ideally in distributed or big-data environments (e.g., Spark, Databricks, BigQuery, Snowflake, similar)

  • Strong understanding of big data concepts, data pipelines, data cleaning/normalization, and data modeling.

  • Demonstrated ability to partner effectively with engineering, data science, and analytics teams on deeply technical problem spaces.

  • Experience driving large internal initiatives with multiple stakeholders and managing substantial cross-functional dependencies.

  • Proven ability to structure ambiguous requirements, prioritize effectively, and deliver predictable execution on complex technical programs.

  • Excellent communication skills, with the ability to explain technical concepts to diverse audiences and facilitate alignment across teams.

  • A forward-looking, durability-focused mindset—ensuring internal systems and datasets are built for scale, maintainability, and long-term adaptability.

Salary Range:
  • $180,000/year - $230,000/year + equity + benefits

Perks:
  • Employer paid group health insurance for you and your dependents

  • 401(k) plan with employer match (or equivalent for non US-based roles)

  • Flexible paid time off

  • Regular company-wide in-person events

  • Home office stipend, and more!

Corporate Values:
  • Follow Through

  • Deep Understanding

  • Whatever It Takes

  • Do Something Smart

Top Skills

BigQuery
Databricks
Snowflake
Spark

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