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CertifyOS

Staff Data Platform Engineer

Posted 7 days ago
10+ years experience
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AI Summary

You will lead a team of engineers to design and operate a scalable data platform that serves as the source of truth for provider data. This includes managing data architecture, ensuring data reliability and quality, and building foundations for AI/ML workloads.

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Today, healthcare organizations rely on fragmented and outdated provider data.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

We're hiring a Staff Data Platform Engineer to own the data platform that makes CertifyOS the source of truth for provider data. You'll set the architecture, lead a team of engineers to deliver it, and be accountable for the reliability, freshness, and cost of our data.

What You’ll Do

  • Lead a team of engineers to deliver data platform initiatives end to end

  • Own data architecture across OLTP, OLAP, and NoSQL stores (Aurora PostgreSQL, Redshift, MongoDB)

  • Design and operate distributed real-time and batch pipelines in Python and PySpark (Kafka, Kinesis, SNS/SQS)

  • Lead entity resolution and MDM architecture for provider data

  • Build and own data products with clear contracts, SLAs, and consumers

  • Be accountable for data reliability, freshness, quality, and cost, with the observability to prove it

  • Drive performance and scale work: profile, benchmark, and re-architect as volume grows

  • Build the data foundations for AI/ML workloads

  • Mentor engineers, raise the bar on design and code review, and partner with product, analytics, and ML

  • Join the on-call rotation and turn incidents into systemic fixes



What We’re Looking For

  • 10+ years building production data systems, including Staff or Tech Lead scope

  • Led a team of engineers to deliver complex data systems

  • Expert Python and production PySpark

  • Deep distributed systems knowledge: consistency, partitioning, idempotency, backpressure, failure handling

  • Significant entity resolution and MDM experience: matching, deduplication, survivorship, golden records at scale

  • Built and owned data products used by other teams

  • Shipped measurable performance and scale improvements

  • Expertise across OLTP (Aurora, PostgreSQL, MySQL), OLAP (Redshift, Athena, Snowflake, ClickHouse), and NoSQL (MongoDB, DynamoDB, Cassandra)

  • Stream processing and event-driven architecture (Kafka, Kinesis, SNS/SQS)

  • Data observability in practice: quality checks, lineage, monitoring, alerting

  • Built data platforms that serve ML workloads

  • Influences technical direction across teams and communicates clearly with non-technical stakeholders

  • Experience handling sensitive data (PII/PHI)

  • Fluent with AI-assisted development (Cursor, Claude Code, MCP)

Nice to Have

  • Change Data Capture (CDC) patterns

  • Data mesh or data-platform-as-a-product approaches

  • Schema registries or data catalogs

  • Orchestration tools (AWS Glue, EMR, Managed Flink, Airflow/MWAA, dbt)

  • Healthcare or other regulated environments


Technologies & Tools

  • OLTP: Aurora, RDS PostgreSQL

  • OLAP: Redshift, Athena

  • NoSQL: MongoDB Atlas

  • Streaming: Kafka (MSK), Kinesis, SNS/SQS

  • Python and PySpark

  • AWS, Docker, Kubernetes (EKS)

  • GitHub Actions

  • Sentry and data observability tooling

  • Cursor, Claude Code, Codex

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.

If you require reasonable accommodations during the application process, please contact recruiting@certifyos.com.

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

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