Senior Quantitative Data Engineer

YipitData

13d • Remote

About The Position

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.

Requirements

• 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 track record building and maintaining large-scale ETL pipelines using Python and distributed data technologies (e.g., Spark, Airflow, Snowflake, Databricks).
• Experience working with financial, alternative, or time-series data used in quantitative investment workflows.
• Strong understanding of data modeling, schema design, and metadata management.
• Familiarity with cloud-based data infrastructure (AWS preferred).
• Experience with data delivery systems such as S3 feeds, APIs, or data sharing platforms such as Snowflake Share or Delta Sharing.
• Deep curiosity about financial markets and a passion for data-driven investing.
• Strong communication skills and a collaborative mindset, with the ability to translate between technical and research stakeholders.
• A passion for data reliability, reproducibility, and performance.

Responsibilities

• 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).

Benefits

• Our compensation package includes comprehensive benefits, perks, equity, and a competitive salary:
• We care about your personal life, and we mean it. We offer flexible work hours, flexible vacation, a generous 401K match, parental leave, team events, wellness budget, learning reimbursement, and more!
• Your growth at YipitData is determined by your impact, not by tenure, unnecessary facetime, or office politics. Everyone at YipitData is empowered to learn, self-improve, and master their skills in an environment focused on ownership, respect, and trust.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 501-1,000 employees