Top Data & Analytics Jobs

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead technical architecture and roadmap for analytics engineering: design semantic/metrics layer, build AI-ready Snowflake data foundation, optimize dbt projects, mentor engineers, partner with Data Science/Engineering, and champion data governance, observability, and production readiness for AI and downstream analytics.

Design, build, and maintain scalable dimensional data models, semantic/metrics layers, and production data pipelines (dbt, Snowflake). Partner with Data Science, Data Engineering, BI, and DevOps to enable AI/ML, real-time analytics, governance, and data quality while mentoring junior engineers and enforcing best practices.

Lead technical design and architecture for analytics engineering: build and govern the semantic/metrics layer, optimize dbt and Snowflake for performance and AI use cases, mentor engineers, partner with Data Science and Engineering, drive data quality, CI/CD, observability, and deployment of third-party data and emerging tooling to support analytics, ML, and agent-based products.

Lead technical architecture and roadmap for analytics engineering, build and govern semantic/metrics layers, optimize dbt and Snowflake performance, mentor engineers, partner with Data Science and Data Engineering to deliver AI-ready data foundations and ensure data quality and governance.

Lead and grow a team of analytics engineers to build an AI-ready, centralized data foundation. Hands-on duties include writing/reviewing SQL and dbt, designing semantic and dimensional data models, driving data quality, observability, testing, and CI/CD, partnering cross-functionally to deliver scalable data products, and recruiting and developing engineering talent.

Design, build, and maintain dimensional data models, semantic layer, and production data transformation pipelines (dbt/Snowflake). Partner with Data Engineering, Data Science, BI, and Product to deliver governed, AI-ready data products, monitor data quality, enable ML features, and coach junior engineers to uphold code and governance standards.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Lead BI analyst leveraging a modern data stack to deliver dashboards, automated reports, and AI-driven insights. Partner with stakeholders to define data needs, build Tableau visualizations, write complex SQL in Snowflake, and integrate Snowflake Intelligence/Claude to automate workflows and enable self-service analytics across the company.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.