Senior Analytics Engineer

Polymarket•New York, NY

11d

About The Position

Polymarket is looking for a Senior Analytics Engineer to own the modeling layer that sits between our raw data and the decisions the business makes with it. You'll join a small, high-ownership team, working alongside our data engineers and data scientists to turn raw trading and application data into the clean, well-defined models and metrics that everyone from growth to finance to market operations builds on. This is a role for someone who cares as much about whether a number is right as whether the query is fast. You'll define what our core metrics mean, build the models that produce them, and make sure the people who depend on them can answer their own questions without a data person in the loop. And you'll do it in a fast-moving environment where new products launch constantly and the business logic behind them changes just as often.

Requirements

7+ years of experience in analytics engineering, data analytics, or a similar role, with production experience owning a modeling layer
Expert SQL. You're comfortable reading, writing, and optimizing complex queries against high-volume datasets
Hands-on experience with dbt or equivalent, Airflow or other orchestration solutions, and a modern cloud warehouse such as Databricks, Snowflake, BigQuery, or ClickHouse
Strong instincts for dimensional modeling and metric design, including the judgment to know when to denormalize
Fluency with BI tooling such as Hex, Looker, or similar, and a bias toward building for self-serve over fulfilling one-off requests
Enough software engineering fundamentals to work comfortably in version control, review others' code, and keep a project maintainable
Genuine interest in the business. You want to know why a metric moved, not just that your model ran.
Comfortable operating in a fast-moving environment where business logic changes frequently and you need to keep pace

Nice To Haves

Familiarity with on-chain data or blockchain analytics
Experience in fintech, crypto, prediction markets, or other data-intensive financial products

Responsibilities

Design and build the dbt models that turn raw platform, on-chain / off-chain trading activity, and third-party data into trusted, well-documented datasets
Own the definitions of our core metrics including volume, traders, retention, acquisition cost, revenue, etc, so that a number means the same thing in every dashboard and every conversation
Partner closely with data engineers on the warehouse layer, including materialized views, incremental models, query performance, and cost
Build and maintain reporting in homegrown Vercel dashboards and Hex that growth, marketing, finance, and markets teams can use self-serve insights
Work directly with stakeholders to translate open-ended questions into models that answer them durably, rather than one-off queries
Write tests and monitoring at the model layer so data quality issues surface before someone finds them in a board deck
Model new products and market types as they launch, keeping the semantic layer in step with a business that changes weekly
Write end-to-end documentation that’s clear and thorough enough that any engineer or analyst on the team can context-switch into your models without friction