Senior Analytics Engineer (AI)

Location: Remote; the company is headquartered in San Francisco, United States.

Expected pay range: $155,000–$170,000 per year, salaried.

Company

hirify.global provides AI-driven post-purchase solutions for retailers, including customer service, returns and exchanges, fulfillment, product and shipping protection, and fraud detection.

What you will do

• Design, build, and maintain scalable data pipelines and architecture across Snowflake, dbt, and AWS.
• Develop integrations with internal systems, merchants, payment platforms, and external partners.
• Build reusable dbt models for analytics, financial systems, reporting, and downstream data consumers.
• Establish data testing, monitoring, validation, documentation, governance, and automated quality controls.
• Partner with Engineering, Analytics, Finance, Operations, and Financial Systems to define data requirements and communicate technical tradeoffs.
• Lead engineering practices across SQL, dbt, code reviews, CI/CD, and AI-assisted development; mentor teammates and improve platform architecture.

Requirements

• 5+ years of experience as an Analytics Engineer, Data Engineer, or in a similar role focused on data infrastructure, analytics, or operational data.
• Expert-level SQL, including complex joins, window functions, advanced transformations, and query optimization across large datasets.
• Strong production experience with dbt and cloud data warehouses, preferably Snowflake, including modeling, testing, documentation, and deployment.
• Deep understanding of dimensional modeling, facts and dimensions, slowly changing dimensions, and incremental models.
• Experience designing and maintaining end-to-end data pipelines from source ingestion through transformation and downstream reporting.
• Experience with Git-based workflows, pull requests, code reviews, CI/CD, and collaborative development.
• Hands-on experience building with AI coding agents such as Claude Code.
• Ability to independently lead technical projects, make architectural decisions, and balance immediate needs with long-term platform improvements.
• Strong communication skills and ability to work effectively with technical and non-technical teams.

Nice to have

• Experience with AWS data services such as S3, Glue, and Lambda.
• Familiarity with infrastructure as code and cloud-based data architecture.
• Working knowledge of Python for automation and validation; the role is SQL/dbt-first.
• Experience working with APIs and external data integrations.

Culture & Benefits

• Collaborative and supportive environment with colleagues from diverse backgrounds.
• Full medical, dental, and vision benefits.
• Stock in an early-stage startup.
• Generous, flexible paid time off policy.
• 401(k) with financial guidance from Morgan Stanley.