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Tier-1 brand, metro location, mid-level generalist data role, and broad tech requirements increase applicant density.
Core data engineering and analytics skills are transferable, but enterprise BI and Microsoft Fabric add some specificity.
Explicit 6+ years and many mandatory technologies (Snowflake, dbt, Airflow, Power BI) create high filter strictness.
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Lead design and delivery of scalable reporting, advanced analytics, and AI/ML data models and pipelines using Snowflake, Microsoft Fabric, Power BI, Python, dbt, and Apache Airflow.
Architect and maintain enterprise semantic models to enable governed self-service analytics with sub-second query performance.
Partner with analytics, data science, and business teams to support AI/ML consumption and drive end-to-end analytics data journeys and adoption.
Minimum 6+ years of corporate experience in data engineering, enterprise analytics, or related technical roles.
Strong hands-on expertise with Snowflake (SnowSQL, Snowpipe), advanced SQL, Python, Microsoft Fabric (OneLake), Power BI, and advanced DAX.
Experience with data modeling (dimensional and semantic), dbt, Apache Airflow, and end-to-end analytics pipeline development.
Experience or exposure to AI/ML platforms, predictive analytics, and preparing data for LLM-based use cases.
Experienced in designing analytics-optimized data models and scalable data pipelines for enterprise reporting and AI/ML workloads.
Skilled at building unified enterprise data layers integrating Snowflake and Microsoft Fabric to support BI, self-service analytics, and AI applications.
Capable of providing technical leadership and collaborating across global, cross-functional teams to drive data strategy and operational analytics platform adoption.