About JSSI
Founded in 1989 and headquartered in Chicago, Jet Support Services, Inc. (JSSI) is the largest independent provider of hourly cost maintenance programs for business aviation. JSSI delivers comprehensive coverage for engines, airframes, and auxiliary power units (APUs) across more than 300 different aircraft makes and models, helping owners and operators stabilize maintenance budgets, maximize aircraft availability, and protect asset value throughout the lifecycle of ownership. JSSI has built a portfolio of complementary business lines designed to simplify the economic and technical complexity of business aviation; these include Maintenance teams, Traxxall maintenance tracking software, Parts & Engines, Conklin aircraft cost and performance data, and Aviation Capital asset-based financing solutions. Together, these offerings support owners, operators, and maintenance providers with integrated tools spanning ownership and maintenance planning, execution, and financial management. With more than 6,500 aircraft supported through programs and software platforms, JSSI leverages its unique independence, unmatched scale, and data-driven insight to deliver customized solutions and support models aligned to the interests of each client — regardless of aircraft platform. JSSI is backed by leading institutional investors GTCR, Genstar Capital, and Blackstone. Learn more at jetsupport.com.
We have built a data platform on Microsoft Fabric and Azure. Our analytics team is consuming data, and our AI roadmap depends on clean, structured, trustworthy data to deliver. What we are missing is the technical owner who makes the data actually work.
This is not a hands-off leadership role. The Director of Data Engineering will be a player-coach: leading and growing a team of 2–5 engineers while remaining a hands-on contributor who can architect solutions, write pipelines, and set the technical bar. You will own the Fabric platform end-to-end, connect our source systems into a reliable data foundation, and serve as the linchpin between raw data and every downstream initiative that depends on it.
Every AI project on our roadmap requires clean, well-structured, trustworthy data. The Fabric platform is in place. This role makes it useful. Without strong data engineering leadership, our analytics team is constrained by data quality issues they cannot fix — and our AI initiatives stall before they start.