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YipitData is a unicorn-valued ($1B+) market research and analytics firm backed by The Carlyle Group, analyzing billions of alternative data points daily to deliver strategic intelligence across software, AI, cloud, e-commerce, ridesharing, and payments sectors.
The Central Data team sits at the foundation of YipitData's operations, building standardized data products, methodologies, and systems that power downstream business units—from investment research and corporate products to data feeds. Historically, teams solved similar data problems independently; Central Data now identifies common patterns and builds shared solutions to improve quality, consistency, and speed company-wide.
As a Central Data Lead, you will own one foundational data domain end-to-end in a highly analytical product ownership role combining deep data expertise, systems thinking, technical leadership, and cross-functional execution. Rather than solving one-off analytical problems, you'll design reusable systems and methodologies enabling dozens of downstream teams to move faster with greater confidence.
You're hiring into one of two domains: Consumer Receipts (owning systems that process, classify, and validate transaction-level consumer receipt data across millions of purchases) or B2B Spend (owning systems transforming complex mid-market and enterprise purchase/invoice data from multiple providers into standardized, production-ready datasets).
Each domain is jointly led by a three-person leadership team: Central Data Lead (methodology, data quality, analytical strategy), Technical Product Manager (prioritization, roadmap, business alignment), and Data Engineering Manager (engineering execution, platform architecture, technical delivery).
You will own the lifecycle of your data domain—from defining how raw partner data should be processed, validated, tagged, and modeled to ensuring downstream teams confidently build products on top of it. You'll develop deep domain expertise and mental models to identify issues before they impact customers. You'll build systems that improve data quality through validation frameworks and monitoring, establish data governance standards, and partner with data evaluation, engineering, downstream product teams, and external data partners.
Success is measured not by analyses completed but by how effectively you've built systems making hundreds of future analyses faster, more consistent, and more reliable. This is a remote-friendly role available across the US, with headquarters in NYC.
