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Strong employer brand and metro location but specialized analytics engineering skills limit applicant pool.
Analytics engineering skills (SQL, dbt, cloud warehouses) are broadly transferable across industries.
Explicit 6+ years requirement and mandatory dbt/warehouse/SQL skills narrow candidate pool.
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Build and maintain end-to-end curated data models and warehouse transformations to support product usage, customer adoption, and go-to-market reporting.
Debug data quality issues across source systems, data pipelines, warehouse models, and BI dashboards to ensure data trustworthiness and accessibility.
Collaborate cross-functionally with product, sales, marketing, finance, and engineering stakeholders to translate business questions into data solutions and support data requests.
6+ years experience in analytics engineering, data engineering, or closely related role.
Strong SQL skills with experience shipping production-grade analytical models.
Hands-on experience with modern cloud data warehouses such as BigQuery, Snowflake, or Redshift.
Experience using transformation frameworks like dbt, SQLMesh, or equivalent.
Experienced in end-to-end data pipeline management and building stable, well-documented analytic data models for enterprise-wide consumption.
Comfortable working directly with diverse stakeholders to define data needs and ensure data solutions meet business requirements.
Operates effectively in a hands-on technical role supporting data governance, documentation, and driving self-service analytics culture.