Senior Product Manager, Data

CertifyOS; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Benefits offered by this job

Health insurance

Unlimited PTO

Wellness leave

Job summary

CertifyOS is building the data infrastructure for next-gen provider tech. As Senior Technical Product Manager, Data, you own strategy and execution for end-to-end data provisioning, ensuring compliant, verifiable provider data across NCQA standards.

You will push toward a productized, self-serve, AI-native experience while partnering with multiple teams. You will shape data pipelines, attribution rules, and governance, balancing speed, accuracy, and cost at scale.

Qualifications

• 5–8 years of experience with at least 3 years in technical product management for data or backend products.
• Strong SQL and data literacy; familiarity with data warehousing (BigQuery a plus).
• Experience turning manual operational workflows into product capabilities.
• AI-native execution: comfortable with Claude Code, Codex, Cursor or similar for prototyping and specs.

Responsibilities

• Sourcing: define data requests and routing rules; record every attempt and raw response.
• Association: define attribution/matching rules and maintain data quality thresholds.
• Across the chain: build explainability and observability to trace data from source to screen.
• Define metrics for data platform effectiveness and monitor data health across applications.

Skills

AI-native

Tech PM (data)

APIs & pipelines

Data acquisition

MDM / identity matching

SQL & data literacy

Data governance

Clear communication

Tools

BigQuery

SQL

Job description

About CertifyOS

CertifyOS is building the data infrastructure that powers modern healthcare.

Today, healthcare organizations rely on fragmented and outdated provider data. This creates unnecessary administrative work, regulatory risk, and higher costs across the system. We’re solving that problem.

Our API-first platform automates provider licensing, enrollment, credentialing, and network monitoring by connecting directly to hundreds of primary data sources. We help healthcare organizations maintain accurate, compliant, and reliable provider networks at scale.

Our vision is simple: One API. One provider ID. Frictionless provider data.

We’re backed by leading investors and built by a team with deep experience in provider data systems. At CertifyOS, we value authenticity, accountability, collaboration, results, and openness to feedback. We’re building a high-ownership team focused on solving real infrastructure problems that impact millions of patients.

About the Role

CertifyOS is building the data infrastructure for the next generation of provider technology. As we scale across Credentialing, Monitoring, Rosters, Provider Network Operations, the biggest bottleneck is no longer just building features - it is making the platform easier for internal teams and customers to configure, operate, and extend safely. As the Senior Technical Product Manager, Data, you will own the strategy and execution for the system that keeps credentialed practitioners continuously compliant with NCQA standards. You'll be accountable for the end-to-end data provisioning experience, the data elements, the quality of that data, and the source veracity that proves historical compliance during audits. The ideal candidate would be comfortable making all provider data pipelines trustworthy, fast, configurable, and cheap to run at scale, while moving the team from a service-driven, manual-review posture toward a productized, self-serve, AI-native one. This role sits at the intersection of platform thinking and technical product expertise. You'll partner closely with the Application Product team, Operations, Implementation and Client Success teams.

What You Will Do

• Sourcing: getting the data

  • Own "detect need" and source routing. Define what triggers a data request (a new file, a monthly monitoring cycle, an expiring element) and the rules that route it to the best source: bulk file, API, scraper, paid vendor, outreach or a human analyst. Every attempt and its raw response is recorded.

  • Own source economics. Know the cost, coverage and latency of every source. Decide when to build a scraper, buy an API or pay for a bulk feed.

• Association: getting it on the right practitioner

  • Own attribution and matching. Define how acquired records are matched to practitioners across identifiers that are often missing or conflicting, including probabilistic matching models. Set the quality bar for false and missed matches, and own the review path for low-confidence results.

  • Own survivorship and Master Data Management governance. Define which source wins for each attribute, and make that configurable. Golden record rules, merge and unmerge, audit trail, and a monitoring and observability loops so matching changes never ship blind.

• Across the chain

  • Build explainability. Anyone in the company should be able to ask why a license is missing, stale or attached to the wrong practitioner, and get a traced answer from source to screen. Partner with engineering on the observability that makes the answer trustworthy.

  • Measure data loss end to end. Build the attribute-level funnel that shows where data drops out between acquisition and the application, and give each application pod a data health metric tied to its own north star.

  • Keep data pipelines stable. Triage pipeline and data escalations, separate one-off fixes from product gaps, and cut the volume of manual re-scrapes and stale-data tickets.

  • Define metrics for data platform effectiveness: Metrics by application and client, source success rate and freshness, % of requests resolved without a human, match precision and recall, % of data errors caught before a client reports them, time to explain a data issue, and external data cost per practitioner.

Must-Haves

• AI-native execution. At home and highly productive in Claude Code, Codex, Cursor or similar. You use them to query data, prototype, write specs and automate your own work, and you know where they fail.

• 5 to 8 years of experience, with at least 3 years with technical product management experience with data products or backend products.

• Technical fluency across APIs, data pipelines, retries and orchestration, and third-party data integrations.

• Hands‑on experience with at least one of: data acquisition, scraping or ingestion; or entity resolution, record linkage, MDM or identity matching.

• Strong SQL and data literacy: completeness and freshness metrics, data modeling basics, warehouse tooling (BigQuery a plus). You query the data yourself before you form an opinion.

• Experience turning manual operational workflows into product capability, and the judgement to say no to one‑off requests.

• Clear written communication. You write specs an engineer and a coding agent can both build from.
  

Nice-to-Haves

• Experience in healthcare technology, provider data management, credentialing, or NCQA/CMS‑regulated data environments.

• Experience with rules/flagging engines, exception-review workflows, or compliance audit tooling.

• Experience building AI-assisted internal tools, agentic triage/resolution, or support copilots.

• Familiarity with BigQuery, embedded analytics, or customer‑facing compliance reporting.

• Background as an engineer or technical implementation lead before PM.

• Startup/high‑growth experience in data platform or US SaaS applications

Benefits of Working at Certify

• At Certify, we’re building with intention and taking care of the people doing the work.

• Your well‑being matters to us. We provide 100% coverage of health, dental, and vision insurance premiums for employees. Our US‑based team benefits from unlimited PTO, with at least two weeks off each year to recharge. In India, employees are supported with health insurance, statutory leave benefits, and additional wellness (menstrual) leave for women.

We are an equal opportunity employer committed to building an inclusive environment where everyone feels valued and empowered to do their best work, and we welcome applicants from all backgrounds and experiences.

We are also committed to pay transparency and foster an open culture where compensation conversations are encouraged and respected.