Analytics Engineer

About the role

The Analytics Engineer turns raw product, commercial and vendor data into trusted data products used by teams across Uberall to make decisions. The role owns the transformation layer of the Databricks lakehouse, from curated models through to the datasets and dashboards stakeholders use every day, keeping it reliable, documented and fast.

Key responsibilities

• Curate the data layer: design and build dbt models, apply dimensional modeling, model CDC and third normal form sources, and define naming conventions and project structure
• Build and maintain data products and datasets, deliver reporting in Metabase and Pigment, and enable governed data sharing
• Own production pipelines in Databricks or Apache Airflow, including monitoring, alerting, data quality checks, CI/CD, schema migrations and safe releases
• Tune performance and cost on columnar engines, and maintain documentation, lineage and metadata
• Support vendor and third-party data ingestion as a secondary focus

Required profile

• Proven experience with dimensional modeling and hands-on production experience with dbt
• Understanding of CDC and third normal form modeling for MySQL or PostgreSQL sources
• Experience with lakehouse architecture and Delta Lake
• Experience structuring and orchestrating workflows in Databricks or Apache Airflow
• Production experience with CI/CD, migrations, monitoring and alerting
• Experience with AWS and Databricks, and tuning columnar engines
• Visualization experience with Metabase, Pigment or similar tools
• Ability to explain technical trade-offs to non-technical colleagues and to plan complex work independently

Required skills

• SQL and Python
• Git, Linux shell and code review workflows
• Data quality processes; familiarity with data contracts and semantic layers is a plus