Senior Analytics Engineer

Arena Club•Los Angeles, CA

5h•$130,000 - $165,000

About The Position

This is a hands-on data role for someone who can work independently while partnering closely with data leadership. You'll build, maintain, and extend Arena Club's modern data stack, from ingestion through transformation to the BI layer, taking projects from an ambiguous business question to a production-ready solution. Working cross-functionally with marketing, operations, finance, product, data engineering, and CX, you'll act as the connective tissue between business stakeholders and our data engineering function, delivering well-rounded insights that help reimagine how the world collects, trades, and invests in collectibles.

Requirements

5+ years' experience in analytics engineering, data engineering, or a related data role with direct experience building on a modern data stack
Bachelor's degree (ideally in a quantitative discipline)
Proficient in SQL (Snowflake, Databricks, Big Query, etc.)
Production experience owning or significantly contributing to a dbt project, with strong data modeling skills
2+ years of experience with an ELT/ingestion tool (Fivetran, etc.)
2+ years of experience with data visualization/BI tools (Looker, Omni, Tableau, etc.)
Hands-on experience integrating AI into the modern data stack (e.g., Claude, Claude Code, ChatGPT Enterprise, or Snowflake Cortex)
Proven ability to act as a liaison between technical and business teams, translating stakeholder needs into durable data solutions
Strong analytical and problem-solving skills
Strong communication, both verbal and written
Able to manage multiple priorities across stakeholders

Nice To Haves

Experience with R or Python
Experience with grading, authentication, or collectibles marketplaces

Responsibilities

Build, maintain, and extend Arena Club's modern data stack, including the ingestion layer. Manage connectors, monitor sync health, and onboard new sources to ensure data accuracy and completeness for reporting and analysis.
Develop and maintain our dbt project, including modeling, testing, and documentation. Uphold the standards and conventions that keep our transformation layer reliable and scalable as the team grows.
Manage and build out our business intelligence platform, including its data models, governance, dashboards, and adoption, so stakeholders across the company can self-serve trustworthy insights.
Partner cross-functionally to understand unique data needs, gather requirements, prioritize work, and develop and implement metrics. Drive the buildout of new data across the organization, expanding both the breadth and granularity of what we capture and model.
Serve as the liaison between the business and data engineering, translating business questions into reusable datasets and ensuring engineering investment maps to real business needs.