Senior Data Engineer

Collections runs like an emergency room. You show up in crisis, get triaged by a stranger who doesn't know your history and leave with no follow-up. We're turning it into primary care for consumer finance. We started in the hardest, most broken stage, because if it works there it works anywhere.
70 million Americans fall behind on a debt every year. Most want to pay what they owe and can't find a way back. We've serviced over $20 billion in debt across more than 20 million consumers. We see more people with charged-off loans each year than all but the top five US banks. They rate us about 50% higher than the banks that lent them the money. Creditors net over 30% more with us because we collect more and charge less.
Most AI strips the human out of the work. We use it to do the opposite. In someone's hardest financial moment we make the experience more human. The more human we make it, the more people recover. Now we're moving upstream, catching people before they default and building across every stage of the consumer credit lifecycle. The consumer in collections today is the consumer who gets approved tomorrow.

As January's founding Senior Data Engineer, you'll transform how we leverage data to expand access to credit — not by fixing what's broken, but by unlocking what's possible. 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 that anticipates and enables our most ambitious data initiatives. You'll design the data infrastructure that helps millions achieve financial stability, ensuring every insight flows seamlessly from production to decision-makers. By establishing data engineering as a core discipline at January, you'll free our analysts to focus on insights while you architect the scalable foundation that powers our next phase of growth.

• Own and optimize our entire data platform — taking our Snowflake warehouse from analyst-maintained to engineer-optimized while standardizing data models for customer reporting, operational dashboards, and ML features

• Build self-healing data pipelines — designing ETL processes that scale automatically with volume, implementing monitoring that catches issues before anyone notices, and optimizing costs without sacrificing performance

• Democratize data access — creating intuitive models that help PMs, analysts, and ops teams find answers independently while maintaining security and compliance requirements

• Bridge engineering and analytics — establishing feedback loops between production systems and analytical needs, ensuring schema changes don't break downstream dependencies, and influencing how new features generate data

• Institute modern data practices — implementing testing frameworks, building CI/CD pipelines for infrastructure changes, and creating documentation that enables others to extend your work

• Drive strategic infrastructure decisions — identifying where new tools unlock capabilities, balancing quick wins with architectural vision, and building the foundation for an eventual data engineering team

• Deliver immediate impact through key projects including:

  • Data Model Redesign: Architect unified models that reduce query redundancy for client reporting by 50% while maintaining flexibility

  • Pipeline Reliability: Strengthen monitoring systems to catch 99% of issues before they impact users

  • Cost Optimization: Reduce our Snowflake spend by 30-40% through intelligent clustering and lifecycle management

  • Analytics Enablement: Create semantic layers that enable technical and non-technical users alike to easily extract value from rich user data

• 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 optimization

• Advanced SQL skills — you can write elegant queries and debug why that 45-minute monster is destroying our compute budget

• Production experience with dbt or similar transformation tools, including testing and documentation best practices

• Proven ability to build and maintain ETL/ELT pipelines at scale using modern orchestration tools

• Track record of designing data models that balance analytical flexibility with performance at scale

• Experience as a sole or lead data engineer, owning infrastructure end-to-end without a large team

• History of partnering with engineering teams to improve data quality at the source

• Demonstrated success in reducing infrastructure costs while improving performance

• Experience implementing data quality frameworks and proactive monitoring systems

• Systems thinker who sees beyond individual pipelines to understand organizational data flow

• Ownership mentality — you build your own roadmap and drive initiatives without waiting for permission

• Strategic perspective that connects technical decisions to business outcomes

• Collaborative approach to working with analysts, engineers, and product managers

• Clear communicator who writes documentation people actually read

• Bias toward shipping iteratively rather than pursuing perfection

• 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

• Decentralization beats control. The best calls get made by the people closest to them, not routed up a chain. You'll set the standards that let the team decide without you in the room.

• Speed beats perfection. You run tight loops, act at 70% on reversible calls and adjust as you learn. Fast loops beat slow ones.

• Candor beats comfort. You'd rather hear a hard truth early than a polite sidestep that wastes everyone's time.

• Writing beats the average meeting. Clarity scales.

• AI runs through everything here. We built our own code reviewer that beats the alternatives. Our voice AI handles most inbound calls with zero hallucinated payments. Engineers ship 3-4x the PRs they used to. You'll push it further into the work than almost any company you've worked at.

• We operate at every altitude. No one here lives only on Mount Olympus, not even the leaders. We get into the trenches to learn the ground truth, then refine our information flows so ground truth climbs as fast as direction comes down.

• We build in person, at least three days a week in our office in Nolita, with a growing group coming in every day. Random run-ins cross-pollinate ideas. Face time builds trust no thread can. Building alongside people makes work far more fun.

We are currently hiring for this position in our New York office.

As a New York City-based company, we are dedicated to transparent, fair, and equitable compensation practices that reflect our commitment to fostering an environment where all team members are valued and supported. We encourage individuals from all backgrounds to apply.

We are an equal opportunity employer committed to diversity and inclusion in the workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, age, veteran status, or any other legally protected characteristic.