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Analytics Engineer

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Summary

Owns the dbt transformation layer of Uberall's Databricks lakehouse: designs dimensional data models and curated datasets, builds dashboards in Metabase and Pigment, and keeps production pipelines healthy with CI/CD, monitoring, and data quality checks. Core stack: dbt, SQL, Python, Databricks/Airflow, Delta Lake.

Uberall is seeking an Analytics Engineer to own the transformation layer of their Databricks lakehouse. This role designs and builds data models, curated datasets, and dashboards that enable teams across the organization to make data-driven decisions, while maintaining reliability, documentation, and performance.

What You'll Do

  • Design and build dbt models that transform raw product, commercial, and vendor data into trusted curated data using dimensional modeling principles
  • Build and maintain data products and datasets for internal stakeholders, delivering clear reporting in Metabase and Pigment
  • Own the health of production data pipelines orchestrated in Databricks or Apache Airflow, including monitoring, alerting, and data quality checks
  • Establish reusable development patterns, code review standards, model documentation, and governance standards across the data team
  • Manage CI/CD pipelines, schema migrations, performance tuning, and safe releases of data workloads on columnar engines

What You Need

  • Proven production experience with dbt and dimensional modeling for analytics warehouses
  • Strong SQL and practical Python skills, with comfort using Git, Linux shell, and code review workflows
  • Hands‑on experience with lakehouse architecture, Delta Lake, and columnar engine performance tuning
  • Production experience structuring and orchestrating workflows in Databricks or Apache Airflow with CI/CD, migrations, monitoring, and alerting
  • Understanding of CDC and third normal form modeling for MySQL or PostgreSQL sources

Nice to Have

  • Experience with data quality processes, data contracts, and semantic layers
  • Visualization experience with tools beyond Metabase or Pigment
  • Experience loading and managing vendor and third‑party data sources
  • Proficiency using AI coding assistants for SQL, dbt, and Python development
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