Databricks Lakehouse Lead & Platform Architect

Capgemini Invent; Województwo mazowieckie; Hybrid; PLN 480,000 - 640,000; Full time

Benefits offered by this job

Yearly financial bonus

Private medical care (Medicover)

Life insurance

NAIS benefit platform access

Hybrid working model

Extensive training tracks

Job summary

Capgemini Invent seeks a senior Databricks leader to own lakehouse architecture, guide end-to-end Databricks programs, and drive platform performance and cost optimisation. You will lead a growing engineering team, shape bids, and collaborate with data governance to ensure robust, auditable data platforms across Azure first, with AWS/GCP as needed.

You will work across clouds, design scalable data products, and mentor engineers in a fast-growing practice that delivers cutting-edge data,

Qualifications

• 8+ years in data engineering or data architecture with leadership experience.

Responsibilities

• Own the lakehouse architecture on client engagements: account and workspace design, networking and identity, Unity Catalog, data model, compute and cost strategy, CI/CD.
• Lead Databricks programmes end to end: migrations from legacy warehouses and Hadoop, greenfield lakehouse builds, platform hardening and cost reviews; set the engineering standards (code review, testing, Databricks Asset Bundles, Terraform).
• Deliver data engineering, analytics and ML on the platform: ingestion with Lakeflow Connect, pipelines and data products, Databricks SQL and AI/BI, machine learning and generative AI with MLflow and Mosaic AI; performance tuning and cost optimisation.
• Lead and grow the Databricks engineering team: hiring, technical coaching, certification plan, staffing across engagements.
• Run the technical side of bids: solution design, estimates, proofs of concept, sizing and cost models; present architecture choices and their cost to client architects and executives.
• On engagements with our Data & AI Governance practice, make sure governance designs land in the platform: access models in Unity Catalog, lineage and audit evidence, data quality in pipelines, model governance with MLflow.
• Build reusable assets: reference architectures, migration playbooks, ingestion and cost accelerators, platform standards, and the governance-by-design reference architecture developed with the governance team.
• Follow the Databricks roadmap (Lakeflow, Mosaic AI, AI/BI, Lakebase, serverless) and decide what we adopt, when and for which clients.

Skills

Databricks

Lakehouse architecture

Spark

Unity Catalog

Lakeflow pipelines

Terraform

CI/CD

Databricks Asset Bundles

MLflow

Education

Databricks Certified Data Engineer Professional

Tools

Terraform

Databricks Asset Bundles

Unity Catalog

Lakeflow

Delta Live Tables

Job description

Capgemini Invent seeks a senior Databricks leader to own lakehouse architecture, guide end-to-end Databricks programs, and drive platform performance and cost optimisation. You will lead a growing engineering team, shape bids, and collaborate with data governance to ensure robust, auditable data platforms across Azure first, with AWS/GCP as needed.

You will work across clouds, design scalable data products, and mentor engineers in a fast-growing practice that delivers cutting-edge data,