Senior Quantitative Data Engineer

About Us:

YipitData is the leading market research and analytics firm for the disruptive economy and most recently raised $475M from The Carlyle Group at a valuation of over $1B. Every day, our proprietary technology analyzes billions of alternative data points to uncover actionable insights across sectors like software, AI, cloud, e-commerce, ridesharing, and payments.

Our data and research teams transform raw data into strategic intelligence, delivering accurate, timely, and deeply contextualized analysis that our customers—ranging from the world’s top investment funds to Fortune 500 companies—depend on to drive high-stakes decisions. From sourcing and licensing novel datasets to rigorous analysis and expert narrative framing, our teams ensure clients get not just data, but clarity and confidence.

We operate globally with offices in the US (NYC, Austin, Miami, Mountain View), APAC (Hong Kong, Shanghai, Beijing, Guangzhou, Singapore), and India. Our award-winning, people-centric culture—recognized by Inc. as a Best Workplace for three consecutive years—emphasizes transparency, ownership, and continuous mastery.

What It’s Like to Work at YipitData:

YipitData isn’t a place for coasting—it’s a launchpad for ambitious, impact-driven professionals.

From day one, you’ll take the lead on meaningful work, accelerate your growth, and gain exposure that shapes careers.

Why Top Talent Chooses YipitData:

• Ownership That Matters: You’ll lead high-impact projects with real business outcomes
• Rapid Growth: We compress years of learning into months
• Merit Over Titles: Trust and responsibility are earned through execution, not tenure
• Velocity with Purpose: We move fast, support each other, and aim high—always with purpose and intention

If your ambition is matched by your work ethic—and you're hungry for a place where growth, impact, and ownership are the norm—YipitData might be the opportunity you’ve been waiting for.

About the Role

We are seeking a Senior Quant Data Engineer to join our Data Engineering team, supporting our initiative to build and deliver systematic, data-driven products designed for quantitative investment firms.

This is a high-impact role at the intersection of engineering, quantitative research, and data productization. You will report to the Head of Data Engineering and partner closely with our Quant Research and Product teams to design, build, and scale robust data pipelines that feed quantitative models and data products used by some of the world’s most sophisticated investors.

The ideal candidate has deep experience with large-scale data systems, quantitative data processing, and the rigor required to meet the expectations of institutional quant clients.

This is a senior, hands-on engineering role with the opportunity to shape the foundation of YipitData’s quantitative product strategy.

What You’ll Do:

• Design, build, and operate scalable, efficient data pipelines that integrate and standardize internal and third-party alternative/financial data into analysis-ready formats to support systematic investment research.
• Partner with Quant Research, Data Infrastructure, Product, and Revenue to align pipelines, model/data requirements, and client SLAs.
• Architect PIT-compliant, look-ahead, and leakage-free datasets for quant research/backtesting. Implement PIT-aware “as-of” version backfills and robust handling of late-arriving data. Build data integrity checks for time-series/panel datasets, including de-duplication and outlier/anomaly detection.
• Develop robust data validation and monitoring systems to ensure accuracy, timeliness, and reproducibility of all delivered datasets.
• Implement and optimize data feeds for external delivery to quant clients (APIs, S3, real-time streaming).
• Contribute to product discovery and R&D, helping define the data architecture and infrastructure strategy for the Quant initiative.
• Ensure compliance with and adherence to governance best practices (versioning, documentation, access controls).

You Are Likely to Succeed If You Have:

• 6+ years of experience as a Data Engineer or Quantitative Data Engineer at a financial firm, data provider, or technology company.
• Strong communicator with experience working with both internal and external stakeholders.
• Proven