Senior Analytics Engineer

About the Company

An AI-powered fintech platform that has processed a massive volume of consumer debt and engaged a large base of consumers, significantly outperforming traditional collection approaches in its space. The company is now growing beyond its original product into a broader, multi-product platform, backed by Series B funding, with more than 100 people working out of New York City.

About the Role

This is a founding-level seat owning everything from the gold layer onward: semantic layers, metric definitions, data contracts, and cross-team metrics standardization. Data Engineering owns raw ingestion and warehouse reliability; this person picks up from there and makes sure a metric like "recovery rate" means the same thing whether it's queried in a BI tool, a chatbot, or eventually an AI agent. It's as much a governance and cross-team influence role as a technical one.

What You'll Own

• The gold layer and a Snowflake-native, dbt-driven semantic layer, feeding BI tools, internal tools, and future chatbot or AI-agent interfaces from a single certified source
• Defining and enforcing data contracts and standardized metrics, resolving cross-team disagreement about what a metric actually means
• Partnering with Data Engineering on client-facing reporting work, clarifying metric definitions and building the models a new reporting experience needs
• Advocating to expand the data the company captures, partnering across teams to close data-capture gaps
• Cost management for the data warehouse and analytics tooling powering the gold layer
• Building certified, well-documented data products that let analysts, PMs, ops teams, and eventually AI agents get correct answers without pinging a data scientist

What We're Looking For

• 5 or more years in analytics engineering, data analytics, or a closely related analytics role. Data engineering experience is a nice-to-have here, not the primary background, this is an important distinction: resumes dominated by orchestration and infrastructure keywords with limited SQL or dbt fluency are not the right fit for this seat specifically
• Advanced SQL, clearly evidenced in your resume or work history, not just listed as a skill
• A track record owning or leading metric or data-modeling work as the sole or lead analytics engineer, not just contributing to a larger, engineering-owned pipeline
• Experience defining metrics or data contracts that multiple teams actually adopted, and navigating real cross-team disagreement about what those metrics mean
• Bonus: strong dbt experience, a named semantic-layer tool (dbt Semantic Layer, Cube, LookML, Looker), a BI or self-serve tool like Sigma, experience building data products for LLM-based or agentic consumers, or direct experience optimizing data-warehouse costs

Logistics

New York City, hybrid. Compensation is $180K to $211.5K plus equity. Visa sponsorship is not available for new visas in this role. Visa transfers are considered case by case. If you are based outside New York, you would need to relocate within 60 days of starting.