Lead Data Engineer
What is Coast Coast is re-imagining the trillion-dollar U.S. B2B card payments infrastructure, with a focus on the country’s 500,000 commercial fleets, 40 million commercial vehicles, and many millions of commercial drivers. The incumbent technologies that cater to these customers are decades old, and businesses with fleets increasingly demand modern digital experiences and transparent financial services products. Coast’s mission is to deliver this at a transformational scale, beginning with the Coast Fleet and Fuel Card built on a cutting-edge spend management platform. About the Role We are looking for a leader of the Coast data engineering team to shape our company’s data culture and underlying infrastructure. At Coast, the success of our data platform is driving accelerating demand from all corners of the company. We’re looking for a key builder to help us meet this moment. In this role, you will drive the evolution of our modern, cloud-native data platform. This is a chance to lead a small, high-leverage team and make a definitive impact, building the systems that help us understand risk, acquire customers, and create a better financial product. You will be building on a solid foundation that lets you focus on high-impact work from day one. Our data engineering organization follows the federated model of data product ownership—the data platform serves as the foundation, not the first line of defense against data issues. We need you to help us establish a vision for the data ecosystem evolution while satisfying day to day demands of a rapidly growing early stage startup. You will report directly to the Head of Engineering and work from our NYC office. What You’ll Do lead design and implementation of all aspects of our data ecosystem — from obtaining third party data to building our own data products, from infrastructure architecture to end-user BI and data exploration toolchain; evangelize and implement the best practices, from reasoning about statistical significance to granting data access via AI tools, from source control and change management to database migrations; establish guardrails for self-serve ecosystem for the business users; help our product engineering teams evolve from treating data as exhaust to building DDD-based data products; enhance our ETL/ELT patterns, from landing zone to semantic layers; ensure that our metrics are built on top of consistent, curated data with clear stewardship; oversee our connected SaaS data landscape; own the budget for the data infrastructure and develop a sensible cost allocation model; safeguard our data, from tokenization and access controls, to retention and backups; remain relentlessly pragmatic and balance the daily demands or a fast-growing startup business with the needs of a well-managed platform; Requirements have 7-10+ years hands-on experience working across the data ecosystem, from modern ETL/ELT and orchestration to data warehouses and columnar stores, from BI tooling ...