Location: New york

Onsite | Full-time

Compensation: $140K - $220K

We are hiring on behalf of our client, an aggressively growing, well-funded fintech startup (Series A, $27.9M+ raised) on a mission to bring full transparency to global trading. They are replacing the opaque, offshore brokerage model with a transparent, permissionless trading stack built on-chain. By leveraging open, auditable code, we ensure that every trade, deposit, and withdrawal is verifiable. Backed by world-class investors including General Catalyst, Jump, and Susquehanna, they are looking for a Data Engineer to build the analytics engine that will power their next phase of growth.

The Role

As the Data Engineer for Internal Analytics & GTM (Go-To-Market), you will own the data systems that help them understand their users, optimize their growth motion, and drive better decision-making across the business. Your mandate is to turn raw on-chain and product data into reliable, self-serve analytics that fuel acquisition, retention, and revenue.

What You’ll Do

• Data Pipelines: Architect and maintain robust ingestion and transformation pipelines for on-chain events, product telemetry, and third-party marketing/CRM data using AWS-native services.
• Analytics Infrastructure: Build and own core data models—covering user journeys, cohort analysis, attribution, and LTV—to enable self-serve reporting for Growth and Marketing teams.
• Dashboards & Reporting: Design and maintain high-impact dashboards (Metabase, Looker, or similar) that surface key GTM metrics like activation rates and trading behavior.
• User & Wallet Analytics: Develop frameworks to analyze on-chain wallet behavior (deposit patterns, churn signals) and enrich them with off-chain context.
• Experimentation: Build the data foundations for A/B testing and growth experiments, ensuring clean event tracking and statistical rigor.
• Productionization: Package pipelines into reliable services with CI/CD, automated tests, and data quality checks that the entire stakeholder team can trust.

Requirements

• Engineering Fluency: Strong experience in Python (pandas/polars, dbt) and expert-level SQL.
• Cloud Infrastructure: Hands-on experience with the AWS ecosystem (S3, Athena, Glue, Redshift, Lambda, Step Functions).
• BI & Visualization: Proven ability to build self-serve reporting layers in tools like Metabase, Looker, Preset, or Tableau.
• Production Mindset: Experience turning ad-hoc analysis into robust, versioned pipelines with CI/CD and reproducible environments.

Bonus Points If You Have

• Experience with GTM analytics (attribution modeling, funnel analysis, or marketing mix measurement).
• Familiarity with crypto/DeFi data and on-chain event streams (The Graph, Dune, RPC logs).
• Experience with orchestration and data quality tools (Airflow, Dagster, Great Expectations).
• Exposure to product analytics tools like Amplitude, Mixpanel, or Segment.



Benefits

• Competitive Compensation: High-growth salary + equity and token grants.
• Cutting-Edge Tech: Work at the intersection of high-frequency finance and blockchain.
• Talented Team: Collaborate with veterans from top-tier trading and tech firms.
• Flexibility: Remote-first culture with flexible work arrangements.
• Professional Growth: Stipends for development and the opportunity to own a massive vertical of the data stack.