> Markdown version of [/jobs/ext/2462638-gcp-data-platform-engineer](https://www.wearedevelopers.com/jobs/ext/2462638-gcp-data-platform-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # GCP Data Platform Engineer - **Company:** Capgemini - **Location:** Atlanta, GA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Apache HTTP Server, Big Data, System Configuration, Data Architecture, Data Infrastructure, Data Security, Interoperability, Metadata, Role-Based Access Control, Cloud Services, Cloudera, Software Deployment, Google Cloud, Data Lakes - **Published:** August 4, 2026 - **Apply:** https://us.experteer.com/career/view-jobs/gcp-data-platform-engineer-atlanta-ga-usa-58816125 ## About the Role validate the end-to-end architecture * Define and enforce data access governance with RBAC and service account policies across both environments * Lead the full lifecycle from environment setup to production deployment * Publish architecture blueprints and cross-platform interoperability best practices for hybrid data lake implementations Tasks * 5 years of relevant experience in data platform engineering * Hands-on experience with Google Cloud Platform (GCP) * Experience with on-prem Cloudera big data clusters * Experience with Apache Iceberg table format * Experience with Iceberg REST Catalog IRC * Experience with Apache Gravitino for metadata catalog integration * Experience with service account creation and RBAC in hybrid environments Key requirements * Paid time off (vacation, holidays, personal days) * Medical, dental, and vision coverage * Retirement savings plans (401(k) / RRSP) * Life and disability insurance * Employee assistance programs * Local policy-based perks ## Description Experteer Overview In this role you will own the hybrid data platform integration between on-prem Cloudera and Google Cloud. You will establish a repeatable, production-grade pattern for multitenant data architecture starting with GCP as the first cloud tenant. You'll configure foundational infrastructure, governance, and metadata layers to enable secure cross-environment data access. This is a hands-on, end-to-end engineering position that shapes cross-platform data interoperability and scalability within Capgemini's data platform initiatives. Compensation / Benefits * Configure and provision the on-prem Cloudera cluster environment, including service accounts and role definitions for multitenant access * Design and implement Apache Iceberg table structures optimized for hybrid on-prem/cloud workloads * Integrate the Iceberg REST Catalog IRC with Apache Gravitino to unify metadata across environments * Establish GCP as a production tenant on the existing on-prem Cloudera cluster and validate the end-to-end architecture * Define and enforce data access governance with RBAC and service account policies across both environments * Lead the full lifecycle from environment setup to production deployment * Publish architecture blueprints and cross-platform interoperability best practices for hybrid data lake implementations Tasks * 5 years of relevant experience in data platform engineering * Hands-on experience with Google Cloud Platform (GCP) * Experience with on-prem Cloudera big data clusters * Experience with Apache Iceberg table format * Experience with Iceberg REST Catalog IRC * Experience with Apache Gravitino for metadata catalog integration * Experience with service account creation and RBAC in hybrid environments Key requirements * Paid time off (vacation, holidays, personal days) * Medical, dental, and vision coverage * Retirement savings plans (401(k) / RRSP) * Life and disability insurance * Employee assistance programs * Local policy-based perks ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [The Cloud is Calling: Answer with In-Demand Skills](https://www.wearedevelopers.com/videos/945-the-cloud-is-calling-answer-with-in-demand-skills) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Crafting Custom Frameworks with Rust: A Deep Dive into Procedural Macros](https://www.wearedevelopers.com/videos/849-crafting-custom-frameworks-with-rust-a-deep-dive-into-procedural-macros) - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) ## Related Articles - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)