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Salary
$170k – $195k per year
Location
Remote/Hybrid (New York, San Francisco, United States)
Seniority
Senior
Employment
Full-Time
Overview
Company
Impact
Profile match
Imprint is a payments company headquartered in New York City and founded in 2020. The company builds co-branded credit cards and rewards programmes for retailers and brands, running the underwriting, servicing, and app experience in place of a traditional store card issuer. It works with partners including Brooks Brothers, Eddie Bauer, and Westgate Resorts, positioning itself against the legacy private label card business.

Who We Are

Imprint helps the world's best brands grow the lifetime value of their customers. We started with co-branded credit cards and rebuilt them to be smarter, more rewarding, and brand-first. We partner with companies like Crate & Barrel, Rakuten, Booking.com, H-E-B, Fetch, and Shell to launch modern credit programs that deepen loyalty, unlock savings, and drive growth. But the card is just the beginning. We combine advanced payments infrastructure, intelligent underwriting, and deep customer data to create delightful and personalized experiences for members as well as efficient and profitable relationships for our brand partners. Our robust technology and world-class operations allow us and our brand partners to offer powerful financial products without becoming a bank.

In the U.S., co-branded cards alone account for over $300 billion in annual spend, and most still run on decades-old legacy bank systems. Imprint is the modern alternative: flexible, embeddable, and built for how people actually pay today. Backed by Kleiner Perkins, Thrive Capital, Ribbit, and Khosla Ventures, we're building a world-class team to redefine how people pay and how brands grow. If you want to move fast, solve hard problems, and own real outcomes, we want to meet you.

The Opportunity

  • Own the design, development, and delivery of scalable data models, semantic layers, and dashboards that serve business-critical reporting across Imprint

  • Partner directly with Engineering, Product, Finance, Marketing, and Operations to translate ambiguous business questions into reliable, scoped data solutions

  • Build and maintain dbt models that establish consistent, reusable data definitions and reduce ad hoc request volume through self-serve analytics infrastructure

  • Leverage AI-assisted development tools (Claude, Cursor, Copilot) to accelerate implementation, from SQL generation and model scaffolding to automated documentation, while owning the analytical design and validation

  • Own data quality, governance, and documentation practices for BI assets, ensuring dashboards and models are accurate, trustworthy, and discoverable

  • Surface insights proactively by identifying gaps and opportunities in the business, not just responding to inbound requests

  • Evaluate and adopt emerging AI tooling to improve team velocity, contributing to how the BI team integrates AI into its standard workflows

Your Profile

Required

  • Proven experience designing and delivering production-grade data solutions in a complex, high-scale environment

  • Deep SQL proficiency and strong data modeling fundamentals; the ability to read, validate, and direct complex queries matters more than raw writing speed in an AI-assisted workflow

  • Experience with a modern data stack (e.g., Snowflake or Databricks, dbt, Sigma or Looker)

  • Strong ability to work directly with stakeholders, translating ambiguous business questions into clear, scoped data products that non-technical users actually adopt and trust

  • Active experience building with AI tools (Claude, Codex, Copilot, Cursor, or similar) integrated into daily analytical and engineering workflows, not just awareness

  • Comfort operating in a fast-moving startup environment where you own projects end-to-end, prioritize based on business impact, and move fluidly between writing production SQL and sitting with stakeholders to define what "good" looks like

Nice to Have

  • Experience in fintech, payments, lending, or regulated financial environments

  • Experience building or scaling BI infrastructure at a high-growth startup, including governance and data quality frameworks from scratch

  • Familiarity with data orchestration tools (e.g., Airflow) and Python or other scripting languages for transformation and automation

  • Experience defining AI-augmented analytics workflows at a team level: AI-assisted code review, automated documentation, prompt-driven data exploration, or agentic patterns like MCP and tool-use applied to data workflows

We don't expect every candidate to check every box. If this role excites you and you bring strong fundamentals, we encourage you to apply.

Stack

Snowflake, dbt, Sigma. SQL as the primary language, with Python for transformation and automation. AWS infrastructure.

Learn More

Learn more about how we build at Imprint on our engineering blog: https://tech.imprint.co/

Perks & Benefits

  • Competitive compensation and equity packages

  • Leading configured work computers of your choice

  • Flexible paid time off

  • Fully covered, high-quality healthcare, including fully covered dependent coverage

  • Additional health coverage includes access to One Medical and the option to enroll in an FSA

  • 20 weeks of paid parental leave for the primary caregiver and 8 weeks for all new parents

  • Access to industry-leading technology across all of our business units, stemming from our philosophy that we should invest in resources for our team that foster innovation, optimization, and productivity

Imprint is committed to a diverse and inclusive workplace. Imprint is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. Imprint welcomes talented individuals from all backgrounds who want to build the future of payments and rewards. If you are passionate about FinTech and eager to grow, let’s move the world forward, together.

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