Staff Data Platform Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇮🇳 India – Remote

⏰ Full Time

🔴 Lead

🚰 Data Engineer

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CertifyOS

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2021

🏥 Healthcare

☁️ SaaS

🤝 B2B

💰 $40M Series B - Certify on 2025-06

Healthcare • SaaS • B2B

CertifyOS is a healthcare-focused provider data platform that consolidates and verifies provider information to create a single, AI-enabled source of truth. It replaces spreadsheets and point solutions with infrastructure for credentialing, contracting, payments, compliance, and provider data management, offering services like credentialing, licensing, monitoring, and roster management. The platform ingests rosters and real-time feeds, validates records against thousands of sources, and delivers a continuous, clean data stream accessible via one API. CertifyOS is positioned as a B2B SaaS solution for health plans, digital health companies, and health systems, claiming measurable operational improvements (e. g. , reduced re-credentialing costs, faster onboarding) and listing major health plans among its clients.

📋 Description

• Lead a team of engineers to deliver data platform initiatives end to end • Own data architecture across OLTP, OLAP, and NoSQL stores • Design and operate distributed real-time and batch pipelines in Python and PySpark using 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 observability to prove it • Drive performance and scale work by profiling, benchmarking, and re-architecting as volume grows • Build 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

🎯 Requirements

• 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) • 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

🏖️ Benefits

• 100% coverage of health, dental, and vision insurance premiums for employees • Unlimited PTO for US-based team • At least two weeks off each year to recharge for US-based team • 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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