Senior Analytics Engineer, dbt & Cloud Warehousing
Overview
Own the modeling layer that powers decisions at scale, turning raw trading data into trusted metrics used across growth, finance, and operations. You will join a small, high-ownership team of data engineers and scientists, using dbt, SQL, and modern cloud warehouses like Snowflake and BigQuery. Build the models that define core business metrics, ensure data quality with automated tests, and enable self-serve analytics through Hex and Vercel. This role demands a blend of technical rigor and business curiosity, where you balance query speed with data accuracy in a fast-changing product landscape.
What You'll Do8
- 1Design and build dbt models that transform raw platform, on-chain, and off-chain trading data into trusted, documented datasets.
- 2Define and own the semantics of core metrics like volume, traders, retention, and acquisition cost, ensuring consistency across dashboards.
- 3Partner with data engineers on the warehouse layer, optimizing materialized views, incremental models, and query performance.
- 4Develop self-serve reporting in Vercel and Hex for growth, marketing, finance, and markets teams.
- 5Translate ambiguous stakeholder questions into durable, well-modeled answers, avoiding one-off queries.
- 6Write automated tests and monitoring at the model layer to catch data quality issues before they impact board decks.
- 7Model new products and market types as they launch, keeping the semantic layer aligned with rapidly changing business logic.
- 8Produce end-to-end documentation that allows any engineer or analyst to context-switch into your models without friction.
Requirements10
- 17+ years in analytics engineering or data analytics, with production experience owning a modeling layer.
- 2Expert SQL skills, including reading, writing, and optimizing complex queries on high-volume datasets.
- 3Hands-on experience with dbt, Airflow, and a modern cloud warehouse such as Databricks, Snowflake, BigQuery, or ClickHouse.
- 4Strong instincts for dimensional modeling and metric design, including judgment on when to denormalize.
- 5Fluency with BI tooling like Hex or Looker, with a bias toward building self-serve solutions.
- 6Solid software engineering fundamentals: version control, code review, and maintainable project structure.
- 7Genuine business curiosity, wanting to understand why metrics move, not just that models run.
- 8Comfort operating in a fast-moving environment with frequent changes to business logic.
- 9Plus: familiarity with on-chain data or blockchain analytics.
- 10Plus: experience in fintech, crypto, prediction markets, or data-intensive financial products.
Salary Insight
Salary not disclosed in listing
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