Sr. Cloud Data Platform Engineer

Key Responsibilities: Design, build, and maintain infrastructure-as-code using Terraform across AWS environments supporting data platforms. Configure and manage AWS Lake Formation, including tag-based access control (LF-TBAC), to govern data access at scale. Build and maintain DevOps pipelines that integrate AWS data sources with third-party analytics/ontology platforms (Palantir Foundry and similar).Support data pipeline automation, CI/CD, and infrastructure reliability for production data workloads. Apply data governance and security best practices (RBAC, tagging, markings) across the AWS-to-downstream-platform integration. Collaborate with data engineers, analysts, and platform owners to ensure secure, well-governed data access. Document infrastructure patterns and mentor team members on Terraform and AWS best practices. Required Qualifications5–6 years of professional data engineering / DevOps experience. Strong, hands-on Terraform experience (infrastructure-as-code, modules, state management).Deep AWS experience, with strong understanding of AWS Lake Formation, including tag-based access control (LF-TBAC), and how DevOps pipelines integrate AWS data through Lake Formation with third-party platforms. Strong Python and SQL; comfortable with CI/CD and Git-based workflows. Solid grasp of data governance, access control models, and pipeline automation. Due to ITAR requirements, must be a US citizen or Green Card holder.

Preferred Qualifications: Experience with Palantir Virtual Tables or equivalent concepts on other platforms (Snowflake external tables, Databricks Unity Catalog external tables, BigQuery external/federated tables).Interest in developing deeper Palantir expertise over time. Hands-on experience is not required today, but openness to growing into it is a plus. Prior exposure to Palantir Foundry, Snowflake, Databricks, or BigQuery in a production environment. Experience with streaming or near-real-time data processing (Kafka, Spark Streaming).