Data Engineer, Alternative Data for Delta One

Socket.dev; New York (NY); On-site; USD 225,000 - 250,000; Full time

Job summary

Susquehanna is seeking a Data Engineer to join the Systematic Delta One desk in New York. You will design scalable data pipelines ingested from vendor and alternative sources, transforming raw data into research-ready, time-correct datasets for alpha research and signal development.

The role emphasizes Python data apps, ingestion at scale (S3/SFTP/Snowflake), and collaboration with researchers to evolve datasets and tooling. A strong background in data modeling and batch processing is required.

Qualifications

• 5+ years of experience building Python data applications and pipelines over large historical datasets.
• Experience ingesting and normalizing third-party data at scale (S3/SFTP, cloud data shares such as Snowflake, or APIs).
• Strong SQL and familiarity with modern columnar and analytical tooling (Parquet, Arrow, DuckDB or similar), alongside NumPy, Pandas, or Polars.
• Strong understanding of data modeling, data accuracy, and reproducible research workflows; experience with temporal or versioned data (point-in-time, slowly changing dimensions, bitemporal modeling) strongly preferred.
• Demonstrated success operating production data pipelines: monitoring, alerting, backfill and restatement handling, incident forensics.
• Ability to work closely with researchers and scientists, taking ambiguous ideas and evolving them into robust datasets and scalable workflows.
• Experience applying LLMs to data problems (extraction, classification, entity resolution, data-quality checking) or building LLM-assisted and agentic tooling is a plus.
• Experience with cloud data delivery (AWS S3, Snowflake) is a plus; prior experience in C++ is a plus.
• Experience in quantitative finance or electronic trading environments is a plus but not required.
• An advanced degree in Computer Science, Mathematics, Physics, Computer Engineering, or a related field is a plus

Responsibilities

• Own the end-to-end onboarding of new vendor and alternative datasets: from evaluating samples and data dictionaries with researchers, through building ingestion pipelines, to production monitoring
• Build point-in-time-correct datasets: preserving as-delivered history and handling vendor restatements, revisions, and backfills, so backtests see exactly what was knowable at the time
• Design entity-mapping and reference datasets that connect vendor identifiers to tradable instruments
• Extend the platform beyond tabular feeds: apply LLMs and agentic tooling to extract structure from unstructured vendor material and to automate onboarding, entity-resolution, and data-quality workflows
• Run data-quality and vendor-evaluation studies (coverage, revision behavior, panel stability) that directly inform trial and licensing decisions
• Create research-ready datasets optimized for large-scale historical analysis and backtesting workflows
• Improve the shared ingestion platform and tooling so that each new dataset onboards faster than the last

Skills

Python data apps

Ingest third-party data

SQL + columnar tooling

Temporal/versioned data

Production data pipelines

Collaborate with researchers

LLM data tooling

Cloud data delivery

C++ experience

Quantitative finance domain

Advanced degree

Education

Advanced degree in CS/Math/Physics/CE

Tools

Parquet

Arrow

DuckDB

NumPy

Pandas

Polars

Snowflake

AWS S3

Job description

Susquehanna is seeking a Data Engineer to join the Systematic Delta One desk in New York. You will design scalable data pipelines ingested from vendor and alternative sources, transforming raw data into research-ready, time-correct datasets for alpha research and signal development.

The role emphasizes Python data apps, ingestion at scale (S3/SFTP/Snowflake), and collaboration with researchers to evolve datasets and tooling. A strong background in data modeling and batch processing is required.