Data Engineer (Databricks)

📋 Description

• Design and build production data pipelines and Lakehouse solutions using Databricks, Lakeflow
• Architect data platforms across multi-cloud (AWS/Azure) with Delta Lake and Unity Catalog.
• Develop DLT pipelines, PySpark notebooks, and dbt for reliable data transformations.
• Define data models, APIs, and contracts to power product experiences and AI workflows.
• Collaborate with clients and engineers to translate data challenges into concrete solutions.
• Lead data architecture discussions when needed and adapt approach per project needs.

🎯 Requirements

• 3-5 years data engineering with 2+ years in production Databricks environments (consulting/Delivery
• Strong AWS and Azure knowledge; GCP familiarity a plus.
• Deep Databricks expertise: Lakeflow Declarative Pipelines, Autoloader, Structured Streaming, Unity
• Experience designing Lakehouse architectures and production-grade data pipelines.
• SQL and Python proficiency; data modeling and schema design skills.
• CI/CD for data and testing/observability experience.

🎁 Benefits

• Collaborative, respectful culture with a focus on craft and impact.
• Opportunity to shape Livefront’s Databricks practice and accelerators.
• Competitive compensation and growth-focused environment.