Analytics Engineer

• Design and build dbt models that transform raw sources into trusted curated data
• Apply dimensional modeling to create facts and dimensions for analytics
• Model transactional CDC and third-normal-form sources
• Define and enforce naming conventions and project structure
• Build and maintain datasets and data products for internal stakeholders
• Deliver reporting in Metabase and Pigment
• Translate business questions into data models with stakeholders
• Enable safe, governed data sharing across teams
• Own the health of production pipelines orchestrated in Databricks or Apache Airflow
• Set up monitoring, alerting, and data quality checks
• Manage CI/CD pipelines, schema migrations, and safe releases
• Tune workload performance and costs on columnar engines
• Establish reusable development patterns and code review standards
• Maintain documentation, lineage, and column-level metadata
• Contribute to governance standards and data contracts
• Support vendor and third-party data ingestion
• Use AI coding assistants to write, test, refactor, and document SQL, dbt, and Python
• Explore AI for documentation, data quality checks, and self-serve analytics

Explore Analytics Engineer at Uberall. Review requirements and application details.