Staff Data Platform Engineer
At a glance
Senior Data Engineering role at CertifyOS. Remote, India · full-time.
Pay not stated Data Platform Engineer salary
remoteroles summary, based on the employer's posting.
What you'll do
- Set the platform’s data architecture across transactional, analytical and NoSQL databases, then guide engineers through delivery
- Build and run Python and PySpark pipelines for streaming and batch data, including provider matching and master data management
- Define data products for internal users, with clear interfaces and service expectations
- Track reliability, freshness, quality and cost, and improve performance as data volumes grow
- Coach engineers, partner with product, analytics and ML, and turn on-call incidents into lasting fixes
What you bring
- At least ten years building production data systems, including work at Staff or Tech Lead scope
- You have led engineers delivering complex systems and are highly skilled in Python and production PySpark
- You understand distributed systems deeply and have substantial provider entity-matching and master-data experience
- You have owned data products used by other teams and delivered measurable gains in performance and scale
- You have built observable data platforms for ML workloads and can shape technical direction across teams
Who this fits
This senior role suits a hands-on technical leader who can guide engineers while owning platform architecture and operational outcomes. The position is remote in Bengaluru, India, and includes participation in an on-call rotation.
From the employer
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Today, healthcare organizations rely on fragmented and outdated provider data.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.