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We are looking for analytics engineers to own the semantic and modeling layer of our warehouse by transforming raw data into well-defined, trustworthy datasets and metrics. You are obsessed with analytical consistency, designing impactful metrics, and building strong foundations for self-service analytics.
Job Responsibility:
Build and maintain data models, following modular, tested, and version-controlled practices
Partner with domain teams to understand business logic and codify it into reusable models and metrics
Define and document key metrics and data contracts across domains
Collaborate with Data Platform Engineers to optimize query performance and warehouse cost
Automate and maintain data documentation, lineage, and governance standards
Develop guidelines for analytics development, data modeling and structure conventions
Requirements:
Expertise with SQL, dbt, SQLMesh or similar tools (data modeling, testing, macros, docs)
Experience with data warehousing concepts, cloud warehouses (Snowflake, BigQuery, Redshift, Databricks) and BI tools (Looker, Tableau, Power BI, Hex, Metabase, etc)
Understanding of dimensional modeling, data contracts, and metrics/semantical layers
Familiarity with modern ELT and orchestration workflows (Airflow, Dagster, Prefect, etc)
Strong business acumen and ability to translate domain logic into scalable data structures