Senior Data Engineer

Imprint is reimagining co-branded credit cards & financial products to be smarter, more rewarding, and truly brand-first. We partner with companies like Crate & Barrel, Rakuten, Booking.com, H-E-B, Fetch, and Brooks Brothers to launch modern credit programs that deepen loyalty, unlock savings, and drive growth. Our platform combines advanced payments infrastructure, intelligent underwriting, and seamless UX to help brands offer powerful financial products—without becoming a bank.

Co-branded cards account for over $300 billion in U.S. annual spend—but most are still powered by legacy banks. Imprint is the modern alternative: flexible, tech-forward, and built for today’s consumer. Backed by Kleiner Perkins, Thrive Capital, and Khosla Ventures, we’re building a world-class team to redefine how people pay—and how brands grow. If you want to work fast, solve hard problems, and make a real impact, we’d love to meet you.

Learn more about us on Imprint's Technology blog.

The Data Engineering team at Imprint is responsible for building and scaling the data infrastructure that supports product development, analytics, operations, and machine learning across the company. We own the pipelines, platforms, and processes that empower our stakeholders to trust and act on our data.

We’re looking for a Senior Data Engineer to help evolve our modern data stack and deliver reliable, scalable data solutions. Your work will directly power decision-making and innovation across the business—from financial operations to real-time personalization.

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  Design, build, and maintain scalable data pipelines and infrastructure across batch and streaming systems.

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  Own core components of Imprint’s data stack, including Snowflake, dbt Cloud, Change Data Capture frameworks, and reverse ETL integrations.

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  Develop and enforce best practices in data modeling, testing, observability, and governance.

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  Partner with stakeholders across Product, Analytics, Finance, and Engineering to ensure timely and accurate data delivery.

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  Work on external data integrations, such as partner-facing data shares (e.g., S3, SFTP, Snowflake) and financial reporting pipelines (e.g., with Netsuite).

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  Contribute to architectural decisions for how we scale data infrastructure, including schema design, orchestration, and data lineage.

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  Champion clear documentation, reproducibility, and reliability for critical datasets and workflows.

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  Stay informed about modern data tools and trends and help drive their adoption when appropriate.

• 6+ years of experience in data engineering, analytics engineering, or related roles.

• Expertise in Snowflake and dbt Cloud, with a strong understanding of dimensional modeling and data warehouse best practices.

• Experience working with Change Data Capture (e.g., Fivetran, Hevo), ETL/ELT pipelines, and orchestration frameworks (e.g., dbt Cloud, Airflow).

• Familiarity with reverse ETL tools like Hightouch or Segment, and operational analytics use cases.

• Strong SQL skills and proficiency in Python or a similar programming language.

• A track record of technical ownership and shipping production-grade data systems.

• A detail-oriented mindset and a passion for building clean, maintainable, and observable data systems.

• Strong communication skills and the ability to collaborate effectively with cross-functional partners.

• Experience in fintech, high-growth startups, or customer-facing data products.

• Familiarity with event streaming technologies like Kafka or Kinesis.

• Exposure to data governance, security, or compliance practices.

• Previous work on ML pipelines or experimentation frameworks.