Data Lead

Role Description

YipitData's Central Data team sits at the foundation of everything we deliver. We build the standardized data products, methodologies, and systems that power every downstream business — from our investment research and corporate products to our data feeds.

As a Central Data Lead, you'll own one of these foundational data domains end-to-end. This is a highly analytical product ownership role that combines deep data expertise, systems thinking, technical leadership, and cross-functional execution.

Each domain is jointly led by a three-person leadership team:

• Central Data Lead — owns methodology, data quality, and analytical strategy
• Technical Product Manager — owns prioritization, roadmap, and business alignment
• Data Engineering Manager — owns engineering execution, platform architecture, and technical delivery

We're hiring two Central Data Leads:

• Consumer Receipts - own the systems that process, classify, and validate transaction-level consumer receipt data across millions of purchases.
• B2B Spend - own the systems that transform complex mid-market and enterprise purchase and invoice data from multiple providers into standardized, production-ready datasets.

As Our Central Data Lead 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 can confidently build products on top of it.
• Build systems that improve data quality — Design validation frameworks, monitoring, and QA systems that proactively detect issues.
• Design reusable methodologies that scale — Identify common business concepts and analytical patterns across Investor, Corporate, and Data Feeds.
• Set analytical and technical direction — Partner with the Technical Product Manager to prioritize investments based on cross-business impact.
• Expand and evolve your domain — Partner with the Data Evaluation team to onboard new datasets.
• Redesign analytical work with AI — Use AI, automation, and emerging tooling to fundamentally improve how data is processed.
• Help build the organization — Mentor junior analysts and establish the standards, processes, and culture that define how your domain operates.

Example Projects:

• Design a generalized methodology for classifying millions of receipt line items across multiple data providers.
• Build automated QA systems that detect systematic shifts in merchant tagging before they impact downstream products.
• Develop reusable frameworks that reduce the time required to onboard new datasets from months to weeks.
• Partner with Engineering to redesign processing architecture that improves scalability while reducing operational overhead.
• Create standardized business logic that replaces multiple inconsistent implementations used across different business units.

Qualifications

• 6-8+ years of experience in data analytics, with a background in fields like financial services, management consulting, data science, or high-growth technology.
• Expert fluency in SQL and experience using Python or PySpark, including building reliable, reusable analysis workflows.
• Proven track record of quickly learning complex data methodologies and building strong mental models of how and why data works.
• Experience leading complex, ambiguous projects with multiple stakeholders.
• Ability to calibrate rigor to the stakes of decisions.
• Reason about bias and representativeness, not just averages.
• Skilled at working with messy, inconsistent datasets and evolving schemas.
• Ability to clearly communicate complex concepts and influence cross-functional partners.
• Energized by the prospect of building and mentoring junior analysts.
• Active use of AI tools and excitement about using AI to drive leverage.

Benefits

• Flexible work hours and flexible vacation.
• Generous 401K match.
• Parental leave.
• Team events and wellness budget.
• Learning reimbursement.
• Competitive salary with an annual performance-based bonus of up to 10%.
• Equity included in the compensation package.