Senior Product Manager, Data

CertifyOS

1d

About The Position

CertifyOS is building an API-first data infrastructure platform for healthcare organizations, automating provider licensing, enrollment, credentialing, and network monitoring through connections to primary data sources. The Senior Technical Product Manager, Data will own the strategy and execution of the system that keeps credentialed practitioners continuously compliant with NCQA standards. The role is accountable for end-to-end data provisioning, data elements and quality, and source veracity that demonstrates historical compliance during audits.

This role focuses on making provider data pipelines trustworthy, fast, configurable, and economical at scale, while moving teams from manual, service-driven operations toward productized, self-service, AI-native workflows. It sits at the intersection of platform strategy and technical product expertise and partners closely with Application Product, Operations, Implementation, and Client Success teams.

Requirements

• 5 to 8 years of experience, including at least 3 years in technical product management with data products or backend products.
• Technical fluency across APIs, data pipelines, retries and orchestration, and third-party data integrations.
• Hands-on experience in at least one of data acquisition, scraping or ingestion; or entity resolution, record linkage, MDM or identity matching.
• Strong SQL and data literacy, including completeness and freshness metrics, data-modeling basics, and warehouse tooling; BigQuery is a plus.
• Ability to query data directly before forming an opinion.
• Experience converting manual operational workflows into product capabilities and judgment to say no to one-off requests.
• Clear written communication and ability to write specifications for engineers and coding agents.
• Comfort and high productivity using Claude Code, Codex, Cursor, or similar AI coding tools, including awareness of their limitations.

Nice To Haves

• Experience in healthcare technology, provider data management, credentialing, or NCQA/CMS-regulated data environments.
• Experience with rules or flagging engines, exception-review workflows, or compliance audit tooling.
• Experience building AI-assisted internal tools, agentic triage or resolution, or support copilots.
• Familiarity with BigQuery, embedded analytics, or customer-facing compliance reporting.
• Background as an engineer or technical implementation lead before becoming a product manager.
• Startup or high-growth experience in data platforms or US SaaS applications.

Responsibilities

• Own the process for detecting data needs and routing requests to appropriate sources, such as bulk files, APIs, scrapers, paid vendors, outreach, or human analysts.
• Ensure every data acquisition attempt and its raw response are recorded.
• Manage source economics by understanding source cost, coverage, and latency, and deciding whether to build a scraper, buy an API, or pay for a bulk feed.
• Define attribution and matching of acquired records to practitioners, including probabilistic matching where identifiers are missing or conflicting.
• Set standards for false and missed matches and define review paths for low-confidence results.
• Own survivorship and Master Data Management governance, including configurable source precedence, golden-record rules, merge and unmerge processes, audit trails, monitoring, and observability.
• Build end-to-end explainability so teams can trace why data is missing, stale, or associated with the wrong practitioner, partnering with Engineering on trustworthy observability.
• Measure data loss across the acquisition-to-application funnel and provide each application pod with a data health metric tied to its north-star metric.
• Maintain stable data pipelines by triaging pipeline and data escalations, distinguishing one-off fixes from product gaps, and reducing manual re-scrapes and stale-data tickets.
• Define and track data platform effectiveness metrics, including application- and client-level metrics, source success and freshness, human-free resolution rates, match precision and recall, errors caught before client reports, time to explain data issues, and external data cost per practitioner.
• Use AI coding tools to query data, prototype, write specifications, and automate work, while understanding their limitations.
• Turn manual operational workflows into product capabilities and exercise judgment about declining one-off requests.
• Write clear specifications that engineers and coding agents can build from.

Benefits

• 100% coverage of health, dental, and vision insurance premiums for employees in the US.
• Unlimited PTO for the US-based team, with at least two weeks off each year.
• Health insurance, statutory leave benefits, and additional wellness (menstrual) leave for women in India.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed