Senior Databricks Platform Engineer: Lakehouse Architect

Capgemini Polska; Województwo mazowieckie; Hybrid; PLN 180,000 - 240,000; Full time

Benefits offered by this job

Yearly financial bonus

Private medical care

Life insurance

Training & certifications platform

Hybrid work model

Home office package

Job summary

Capgemini Polska is seeking an experienced Data Engineer to build lakehouse platforms on Databricks for client engagements, covering workspace setup, ingestion, pipelines, data models and ML features. You own workstreams end-to-end and collaborate with architects and governance when required.

You will work across the full stack, applying Spark/SQL, Python and Delta Lake skills, with cloud experience (Azure preferred).

Qualifications

• 3+ years in data engineering with at least one year on Databricks in production.
• Senior level: 5+ years, with hands-on work on at least three of: platform setup, pipelines, data modelling, migration, CI/CD and IaC, performance/cost tuning, leadership of a workstream.

Responsibilities

• Set up and configure Databricks platforms: workspaces, compute policies, Unity Catalog basics, networking and identity.
• Build ingestion and pipelines: Lakeflow Connect/Auto Loader, batch and streaming, Delta Lake medallion model.
• Model data for consumption: data products, Databricks SQL, dashboards, feature tables and model serving with MLflow.
• Migrate workloads from legacy warehouses to Databricks; refactor as needed.
• Use Git and CI/CD; infrastructure as code with Terraform; maintain release processes.
• Run and optimise: monitoring, job orchestration, performance tuning, cost control.
• Support governance: data quality, lineage, access requests in Unity Catalog.
• At senior level: estimate and plan workstreams, support bids, coach engineers, maintain certifications.

Skills

Spark PySpark/Scala

SQL

Python

Databricks

Unity Catalog

Cloud (Azure preferred)

Git

CI/CD

Terraform

Tools

Lakeflow

Auto Loader

Databricks Asset Bundles

Job description

Capgemini Polska is seeking an experienced Data Engineer to build lakehouse platforms on Databricks for client engagements, covering workspace setup, ingestion, pipelines, data models and ML features. You own workstreams end-to-end and collaborate with architects and governance when required.

You will work across the full stack, applying Spark/SQL, Python and Delta Lake skills, with cloud experience (Azure preferred).