Senior Data Engineer

About January At January, we're rebuilding one of the most broken parts of consumer finance: what happens after someone falls behind on debt. Our autonomous, compliant collections platform works directly for creditors, using data and AI to personalize outreach and offer consumers clearer, more compassionate ways to resolve what they owe. January has serviced $20B+ in debt and engaged 20M+ consumers. Backed by Series B funding, ~100+ people working out of Nolita, NYC. About the Role As January's founding Senior Data Engineer, you'll take full ownership of our modern data stack, evolving it from a capable system maintained part-time by analysts and engineers into a world-class platform. By establishing data engineering as a core discipline at January, you'll free analysts to focus on insights while you architect the scalable foundation that powers our next phase of growth. Key Responsibilities - Own and optimise our entire data platform — evolving our Snowflake warehouse and standardising data models for customer reporting, operational dashboards, and ML features - Build self-healing data pipelines — design ETL processes that scale automatically and implement monitoring that catches issues before anyone notices - Democratise data access — create intuitive models that help PMs, analysts, and ops teams find answers independently - Bridge engineering and analytics — establish feedback loops between production systems and analytical needs - Institute modern data practices — implement testing frameworks, build CI/CD pipelines for infrastructure changes - Drive key projects: data model redesign (reduce query redundancy by 50%), pipeline reliability (catch 99% of issues before they impact users), Snowflake cost optimisation (30–40% reduction) Requirements - 5+ years in data engineering or analytics engineering with progressive technical responsibility - Deep expertise with modern data warehouses (Snowflake, BigQuery, or Redshift) including performance tuning and cost optimisation - Advanced SQL skills - Production experience with dbt or similar transformation tools - Proven ability to build and maintain ETL/ELT pipelines at scale using modern orchestration tools - Experience as a sole or lead data engineer, owning infrastructure end-to-end - Experience implementing data quality frameworks and proactive monitoring systems Bonus Skills - Experience with streaming architectures and real-time analytics - Familiarity with ML infrastructure and feature stores - Knowledge of financial data privacy regulations and compliance - Previous startup or high-growth company experience