Data Engineer (Alternative Data)

Location: New York, New York

Annual base pay: $225,000–$250,000 plus discretionary bonus and benefits.

Company

hirify.global is a quantitative trading firm that applies scientific research, machine learning, and advanced technology to global financial markets and derivatives trading.

What you will do

• Onboard vendor and alternative datasets from evaluation and data-dictionary review through ingestion, production monitoring, and ongoing maintenance.
• Build point-in-time-correct datasets that preserve delivered history and handle revisions, restatements, and backfills.
• Design entity-mapping and reference datasets connecting vendor identifiers to tradable instruments.
• Develop pipelines and research tools for structured, semi-structured, and unstructured data, including documents, filings, transcripts, and data dictionaries.
• Apply LLMs and agentic tooling to extraction, entity resolution, onboarding, and data-quality workflows.
• Create research-ready datasets and improve shared ingestion infrastructure for historical analysis and backtesting.

Requirements

• 5+ years of experience building Python data applications and pipelines over large historical datasets.
• Experience ingesting and normalizing third-party or vendor data through S3, SFTP, cloud data shares, or APIs.
• Strong SQL skills and familiarity with Parquet, Arrow, DuckDB, NumPy, Pandas, or Polars.
• Knowledge of data modeling, data accuracy, reproducible research workflows, and temporal or versioned data.
• Production pipeline experience with monitoring, alerting, backfills, restatement handling, and incident forensics.
• Ability to collaborate with quantitative researchers and scientists to turn ambiguous ideas into robust datasets and scalable workflows.

Nice to have

• Experience applying LLMs to extraction, classification, entity resolution, or data-quality checking.
• Experience with AWS S3, Snowflake, or C++.
• Background in quantitative finance or electronic trading.
• Advanced degree in Computer Science, Mathematics, Physics, Computer Engineering, or a related field.

Culture & Benefits

• Close daily collaboration between data engineers, researchers, and traders.
• Direct impact on research datasets, signal development, and production trading strategies.
• Opportunities to learn, innovate, and grow in a scientifically rigorous trading environment.
• Discretionary bonus and employee benefits.
• Flexible start date.