Responsibilities

• Data Enablement: develop core Looker views and build agentic AI infrastructure to reduce reporting bottlenecks and enhance self-service analytics.
• Pipeline Architecture: design, build, and scale ELT pipelines that are resilient, efficient, and modular.
• Cross-Functional Collaboration: partner with Finance, Product, and Analytics to ensure data models solve the right problems.
• Data Modeling: build and maintain analytics schemas (including star schemas) for user-friendly datasets.
• End-to-End Ownership: lead projects from inception to production, ensuring data integrity and trust in the platform.
• Operational Excellence: monitor production health with tools like Datadog and Monte Carlo to keep the data ecosystem robust.
• Technical Leadership: act as technical lead, conduct code reviews, define engineering culture, and champion best practices.

Requirements

• Experience: 5+ years in data engineering, with at least 2+ years in distributed, large-scale cloud data warehouses.
• Snowflake Expertise: strong experience with Snowflake performance optimization and cost governance; familiarity with Snowflake Cortex/MCP is a plus.
• Technical Mastery:
• Advanced Python: strong proficiency in Python with modular, testable code.

Responsibilities

• Data Enablement: develop core Looker views and build agentic AI infrastructure to reduce reporting bottlenecks and enhance self-service analytics.
• Pipeline Architecture: design, build, and scale ELT pipelines that are resilient, efficient, and modular.
• Cross-Functional Collaboration: partner with Finance, Product, and Analytics to ensure data models solve the right problems.
• Data Modeling: build and maintain analytics schemas (including star schemas) for user-friendly datasets.
• End-to-End Ownership: lead projects from inception to production, ensuring data integrity and trust in the platform.
• Operational Excellence: monitor production health with tools like Datadog and Monte Carlo to keep the data ecosystem robust.
• Technical Leadership: act as technical lead, conduct code reviews, define engineering culture, and champion best practices.

Requirements

• Experience: 5+ years in data engineering, with at least 2+ years in distributed, large-scale cloud data warehouses.
• Snowflake Expertise: strong experience with Snowflake performance optimization and cost governance; familiarity with Snowflake Cortex/MCP is a plus.
• Technical Mastery:
• Advanced Python: strong proficiency in Python with modular, testable code.

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