Staff Data Platform Engineer

CertifyOS

13h

About The Position

CertifyOS is hiring a Staff Data Platform Engineer to own the data platform that makes CertifyOS the source of truth for provider data. The role sets data architecture, leads a team of engineers delivering the platform, and is accountable for data reliability, freshness, quality, and cost. The engineer will own architecture across OLTP, OLAP, and NoSQL stores; design and operate real-time and batch pipelines; lead provider-data entity resolution and master data management; and build data products with clear contracts, SLAs, and consumers. The role also drives performance and scale improvements, establishes data foundations for AI/ML workloads, mentors engineers, and partners with product, analytics, and ML teams. The position participates in the on-call rotation and addresses incidents through systemic fixes.

Requirements

10+ years building production data systems, including Staff or Tech Lead scope.
Experience leading a team of engineers to deliver complex data systems.
Expertise in Python and production PySpark.
Deep distributed-systems knowledge, including consistency, partitioning, idempotency, backpressure, and failure handling.
Significant entity resolution and MDM experience, including matching, deduplication, survivorship, and golden records at scale.
Experience building and owning data products used by other teams.
Experience shipping measurable performance and scale improvements.
Expertise across OLTP systems such as Aurora, PostgreSQL, and MySQL; OLAP systems such as Redshift, Athena, Snowflake, and ClickHouse; and NoSQL systems such as MongoDB, DynamoDB, and Cassandra.
Experience with stream processing and event-driven architecture, including Kafka, Kinesis, and SNS/SQS.
Practical data observability experience with quality checks, lineage, monitoring, and alerting.
Experience building data platforms that serve ML workloads.
Ability to influence technical direction across teams and communicate clearly with non-technical stakeholders.
Experience handling sensitive data such as PII/PHI.
Fluency with AI-assisted development tools such as Cursor, Claude Code, and MCP.

Nice To Haves

Experience with Change Data Capture (CDC) patterns.
Familiarity with data mesh or data-platform-as-a-product approaches.
Experience with schema registries or data catalogs.
Experience with orchestration tools such as AWS Glue, EMR, Managed Flink, Airflow/MWAA, or dbt.
Experience in healthcare or other regulated environments.

Responsibilities

Lead a team of engineers to deliver data platform initiatives end to end.
Own data architecture across OLTP, OLAP, and NoSQL stores, including Aurora PostgreSQL, Redshift, and MongoDB.
Design and operate distributed real-time and batch pipelines in Python and PySpark using Kafka, Kinesis, and SNS/SQS.
Lead entity resolution and master data management architecture for provider data.
Build and own data products with clear contracts, SLAs, and consumers.
Ensure data reliability, freshness, quality, and cost, supported by observability.
Drive performance and scale improvements by profiling, benchmarking, and re-architecting as data volume grows.
Build data foundations for AI/ML workloads.
Mentor engineers, raise standards for design and code review, and partner with product, analytics, and ML teams.
Participate in the on-call rotation and turn incidents into systemic fixes.

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 for employees in India.
Statutory leave benefits for employees in India.
Additional wellness (menstrual) leave for women in India.

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