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 and relocation are handled case by case.