Data Engineer
LithicNew York, New York, United States$146k – $230kPosted 20 March 2026
Job Description
Lithic is the modern card issuing and processing platform empowering ambitious financial companies to build the future of payments.
Our infrastructure powers card programs for 100+ innovative clients, from fintechs reimagining credit and digital banking to platforms transforming disbursements and spend management. Companies like Mercury, Flex, and Novo rely on Lithic's developer-friendly APIs, direct network connections, and flawless reconciliation to launch and scale card programs in weeks, not years.
We're building a future where access to better financial products materially improves people's lives, free from the constraints of 30-year-old mainframes and legacy processors. We're proud to be backed by world-class investors who share that vision, including Bessemer Venture Partners, Index Ventures, Spark Capital, Stripes, and Mastercard, along with many others.
We're a team of 160+ across 26 states and 7 countries, headquartered in New York City. Our values (Customer Centricity, Deliver Excellence, Act Like an Owner, Iterate Iterate Iterate, Teach Others, and Be a Good Neighbor) shape how we work and grow as a team.
Lithic is hiring a Data Engineer to join our Infrastructure team and help improve the foundation that the rest of the analytics organization depends on. You’ll own pipelines end-to-end, replace manual work with automated, reliable systems, and partner closely with Finance, Operations, and Analytics to make sure the right data gets to the right people at the right time.
Job responsibilities:
Design, build, and maintain scalable data pipelines that move data reliably from source systems into our Snowflake warehouse
Own and improve our ETL/ELT infrastructure, including tooling, orchestration, monitoring, and data quality validation
Identify and eliminate manual data workflows, replacing them with automated, auditable processes
Partner with the Analytics Engineering team to ensure clean, well-modeled data is available for Finance, Operations, and other business teams
Build and maintain tooling that enables the broader organization to self-serve their data needs
Contribute to data governance practices including access controls, lineage documentation, and data quality standards
Collaborate with software engineers to instrument new systems and bring operational data into our warehouse cleanly
Qualifications:
Strong SQL skills and hands-on experience with modern cloud data warehouses (Snowflake strongly preferred)
Experience building and maintaining production data pipelines using tools like Airbyte, Stitch, Airflow, Prefect, Dagster, or similar
Proficiency in Python and Terraform for data engineering tasks
Familiarity with dbt or similar transformation frameworks
A track record of shipping reliable, well-monitored data systems in production environments
Comfort navigating ambiguity and driving projects forward with minimal oversight
Experience in fintech, payments, or other financial services environments is preferred
Familiarity with AWS services (Lambda, Glue, S3, Step Functions, RDS) is preferred
Experience supporting Finance or Accounting teams and working with financial data concepts (revenue recognition, reconciliation, month-end close) is preferred
Exposure to data platform work including access control, data cataloging, or lineage tooling is preferred
Experience at a company processing high transaction volumes where correctness and reliability are non-negotiable is preferred
The annual US salary range for this role is $146,000 – $230,000 plus equity. This salary range is inclusive of several career levels at Lithic and will be narrowed during the interview process based on the candidate’s experience and qualifications.
Benefits for Full-Time US Employees:
Unlimited PTO
12-weeks fully paid parental leave
4-Week Fully Paid Sabbatical (earned at your 5-year anniversary)
Work From Anywhere: work from anywhere in the world 4-weeks each year
3% cashback on card purchases with your compl ... (truncated, view full listing at source)
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