Senior Analytics Engineer: Modern Data & AI Pipelines

Everpure; Santa Clara (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Flexible time off

Job summary

Pure Storage is seeking a Senior Analytics Engineer to lead end-to-end modernization of analytics, focusing on scalable dbt foundations, data quality, and efficient operations. You will collaborate with BI analysts, RevOps, and engineering partners to transform how analytics are engineered, governed, and consumed.

The role emphasizes building robust data products and AI-enabled workflows, with a strong bias for action and hands-on contribution in a dynamic GTM environment.

Qualifications

• 7+ years of experience in analytics engineering, data engineering, or business intelligence.
• Strong expertise in SQL, Python, Snowflake, and modern ELT development practices.
• Hands-on experience with dbt, orchestration workflows, and scalable data modeling.
• Experience implementing CI/CD, automated testing, observability, and data quality frameworks.
• Strong understanding of semantic modeling, metrics layers, governed metrics, and reusable analytics datasets.
• Experience using AI to build workflows, automate processes, improve operational efficiency, or support business intelligence use cases.
• Ability to influence technical direction while remaining hands-on.
• Strong communication and collaboration skills across technical and business teams.
• Pragmatic interest in applying AI capabilities to real business workflows over time.
• Passion for modernization, reporting trust, and scalable analytics engineering.

Responsibilities

• Lead and contribute hands-on to the team's dbt and Snowflake modernization initiatives.
• Build scalable semantic and metrics layers supporting GTM domains including pipeline, forecasting, quota, attainment, and seller performance.
• Design and maintain robust ELT/ETL pipelines, orchestration workflows, and reusable business-facing datasets.
• Build CI/CD, testing, observability, lineage, and data quality frameworks for analytics engineering workflows.
• Ingest and transform data from APIs and GTM systems into curated canonical datasets with strong quality standards.
• Drive architecture decisions and establish modern analytics engineering best practices across the team.
• Partner closely with BIAs, RevOps, and Systems teams to translate business problems into scalable data products.
• Help automate manual reporting and operational workflows through configurable and scalable frameworks.
• Apply AI capabilities to workflow automation, operational efficiency, and insight generation, while helping lay the foundation for future conversational analytics initiatives.

Job description

Pure Storage is seeking a Senior Analytics Engineer to lead end-to-end modernization of analytics, focusing on scalable dbt foundations, data quality, and efficient operations. You will collaborate with BI analysts, RevOps, and engineering partners to transform how analytics are engineered, governed, and consumed.

The role emphasizes building robust data products and AI-enabled workflows, with a strong bias for action and hands-on contribution in a dynamic GTM environment.