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Polymarket is the world's fastest-growing prediction market platform, enabling users to trade on outcomes across politics, economics, sports, culture, and current affairs. With $115B traded to date, the company is scaling rapidly as an alternative news source and beacon of truth in global media.
As Director of Data Platform, you will lead the teams responsible for building and scaling the data foundation that powers every decision across the company. This includes data engineering, analytics engineering, and data science—owning everything from data ingestion and transformation through the trusted data models the business relies on daily.
You will define the technical architecture, set the roadmap, and build a high-performing organization capable of supporting one of the fastest-growing businesses in technology. As Polymarket launches new products across both on-chain and off-chain systems, the data platform must evolve just as quickly, delivering reliable pipelines, trusted metrics, and an architecture that scales without constant rework.
This is a hands-on leadership role. You'll be deeply involved in technical design, data modeling, and platform strategy while building the team and operating model that enables the company to move faster. Success means creating a platform the business trusts, engineers enjoy building on, and teams can depend on as the company continues to scale.
Key responsibilities include: leading, hiring, and developing a multi-disciplinary team of data engineers, analytics engineers, and data scientists; owning the architecture and roadmap from ingestion through modeled layers; setting standards for data trustworthiness including modeling conventions, testing, and SLAs; partnering with engineering on instrumentation and on-chain data ingestion; prioritizing platform work with analytics leadership and business stakeholders; making build-versus-buy and tooling decisions across the modern data stack; staying ahead of scalability constraints; and building operating rhythms including planning, on-call, and documentation standards.
You should have 10+ years in data engineering, analytics engineering, or data science with 4+ years managing teams. You'll need strong technical foundations across the modern data stack (Airflow, dbt, Spark, Databricks, Snowflake, BigQuery, ClickHouse, AWS, GCP), a track record of raising data quality, and proven hiring and team-building experience. Experience with on-chain data, blockchain infrastructure, fintech, crypto, or prediction markets is a plus.
