DataOps Engineer

Medidata Solutions is seeking a Senior DataOps Engineer to help scale and operate our next-generation clinical data platform. You will work closely with Data Engineering, Data Services and AI/ML teams to automate deployments, enhance observability, and ensure reliable operations for critical pipelines and services powering CTMS, EDC, and eTMF integrations.

What You will Do
Automate deployment and monitoring of Snowflake, Airflow, and S3/Iceberg pipelines across multiple environments.
Build and maintain CI/CD workflows using GitHub Actions and infrastructure as code with Terraform.
Deploy, operate, and scale Python and Java applications on AWS services, including Lambda, ECS, EKS, and Step Functions.
Implement Data observability dashboards, alerts, and incident response workflows.
Operationalize GenAI and Bedrock-integrated pipelines with strong governance and reliability.
Drive root cause analysis, reduce MTTR, and mentor DataOps peers.
What You Bring
Primary
5+ years in DataOps / DevOps / Platform Engineering supporting large-scale data platforms.
Must have: Strong hands-on experience with GitHub Actions, Terraform, and EKS.
Proven track record deploying and managing Python and Java applications on AWS (Lambda, ECS, EKS, Step Functions, CloudWatch, S3).
Expertise in Snowflake, Airflow, and cloud-native data pipeline operations.
Strong scripting and automation skills.
Secondary
Bonus: Experience with Iceberg, data quality frameworks, or GenAI pipeline operations.
Why Medidata
Play a key role in scaling one of Medidatas most critical data platforms.
Work with a modern cloud-native, multi-tenant, GenAI-integrated stack.
Real impact on how global clinical trial data is delivered at scale.