About the Role:
Senior Data Engineer with strong DevOps and cloud infrastructure experience to build and operate the infrastructure and pipelines that support Palantir deployments. This role centers on Terraform-based infrastructure-as-code, AWS data access and governance patterns, especially Lake Formation, and the pipelines that connect AWS-hosted data to Palantir and other analytics/ontology platforms.
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).
