Director, Data Platform

Lead, hire, and develop a team of data engineers, analytics engineers, and data scientists, and set the bar for what good looks like across all three crafts

Own the architecture and roadmap for the data platform, from ingestion through the modeled layer that powers reporting and analysis across the company

Set the standards that make data trustworthy including modeling conventions, testing, freshness SLAs, incident response, and clear ownership of every dataset

Partner with engineering on instrumentation and on-chain data ingestion, so the platform captures what the business needs before someone has to ask for it

Work with analytics leadership and business stakeholders to prioritize platform work against the analyses and decisions it unblocks

Make the build-versus-buy and tooling calls across orchestration, transformation, warehouse, and BI, and own the cost and performance envelope that comes with them

Stay ahead of scalability constraints as volume grows and new products launch, rather than discovering them during an incident

Build the operating rhythm including planning, on-call, review practices, and documentation standards, allowing the team scale past what any one person can hold in their head

10+ years in data engineering, analytics engineering, or data science, including 4+ years managing

Experience leading a multi-disciplinary data team, where engineers and scientists have genuinely different working styles and definitions of done

A strong technical foundation. You can review a data model, an architecture proposal, or a query plan and make it better

Production experience across the modern data stack: orchestration and transformation such as Airflow, dbt, or Spark, a cloud warehouse such as Databricks, Snowflake, BigQuery, or ClickHouse, and AWS or GCP underneath

A track record of raising data quality somewhere the numbers previously could not be relied on, and the judgment to know which fixes actually move trust

Ability to prioritize across competing stakeholders and say no with a reason people can accept

A hiring track record. You have built a team, not only inherited one

Comfortable operating in a fast-moving environment where business logic changes frequently and you need to keep pace

(Plus) Familiarity with on-chain data ingestion or blockchain infrastructure

(Plus) Experience supporting finance or regulatory reporting, where accuracy is not negotiable

(Plus) Experience in fintech, crypto, prediction markets, or other data-intensive financial products

Base salary range: $400,000 to $500,000 annually, plus equity and benefits.

This range reflects a good-faith estimate for this position. Experience levels vary widely within a title here, so please reach out even if your expectations fall outside it. We're always happy to chat.