Analytical Engineer

About This Role

Key ResponsibilitiesAI-extracted

• 1
  Own the Gold layer for a given business domain, designing and continuously improving the curated, dimensional data models that downstream dashboards, Genie spaces, and ELT reporting depend on.
• 2
  Implement the canonical business logic behind your domain's core KPIs, translating KPIs into governed, versioned metric marts that resolve disputes for good.
• 3
  Build and curate the semantic layer and Genie spaces that power self-serve in your domain, authoring metadata, documentation, and prompt/metric definitions.
• 4
  Partner with peers across DS&A to keep KPI definitions consistent where domains overlap, and author data contracts and SLAs at the Silver→Gold boundary.
• 5
  Build and maintain certified, board-ready dashboards on governed Gold data, partnering with Data Science to translate insight requirements into trusted, reusable products.

RequirementsAI-extracted

• 4+ years in analytics engineering, data engineering, or a closely related analytics role, with a track record of independently owning the data models a team relies on for decisions.
• Advanced SQL and strong data modeling fundamentals, including dimensional modeling, star/snowflake schemas, slowly changing dimensions, and semantic layer design.
• Hands-on experience with a transformation framework (dbt or equivalent), orchestration tooling (e.g. Airflow), version control (Git), and modern warehouse/lakehouse platforms (Databricks experience preferred).
• Practical experience with data quality testing and observability, schema management and data contracts, and query/model performance and cost tuning.
• Demonstrated domain fluency in at least one business area and the judgment to translate 'I don't trust this number' into a specific, durable model fix.

Perks & BenefitsAI-extracted