Senior Data Engineer - AI - ETL - Multi Strategy Hedge Fund - NY - Up to $500k TC

Mondrian Alpha

New York (NY)

On-site

USD 300,000 - 500,000

Full time

14 days+

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Job summary

A global investment firm is seeking a Senior Data Engineer to design and optimize ETL/ELT pipelines across various functions. The ideal candidate will have 6+ years of software development experience, with a strong focus on data engineering using Python and SQL. This role operates on a hybrid model in New York, involving close collaboration with quants and traders. Join a lean, high-impact team where you will play a vital role in shaping the firm's data platform.

Qualifications

  • 6+ years of software development experience, including 2+ years focused on data engineering.
  • Strong hands-on ETL/ELT pipeline design and automation experience.
  • Familiarity with modern data transformation and governance/observability tools.

Responsibilities

  • Design, build and optimise ETL/ELT pipelines across various areas.
  • Create and own golden source datasets for downstream reliance.
  • Ensure high data quality, observability and governance.

Skills

Python
SQL
ETL/ELT pipeline design
Data modelling
Docker
Kubernetes

Tools

Postgres
MS SQL Server
Snowflake
Databricks

Job description

Senior Data Engineer - AI - ETL - Multi Strategy Hedge Fund - NY - Up to $500k TC

We’re working with a global investment firm managing over $30bn AUM, which has invested heavily in modernising its data stack and is continuing to grow. This is a chance to be a core Data Engineer in a small, high‑impact team, owning the pipelines and ETL workflows that power trading, research, risk and portfolio decisions end to end.

The Opportunity

You’ll be engineering the backbone of the firm’s data ecosystem: designing and scaling robust, production‑grade data pipelines that feed systematic strategies, risk engines and analytics. You’ll work closely with quants, traders, risk and technology leadership to turn messy, heterogeneous data into clean, trusted, well‑documented “golden sources” that the business can rely on. The firm has recently brought in senior talent from leading systematic platforms such as DRW and Millennium to help drive this build‑out and long‑term data strategy.

What you’ll work on
  • Design, build and optimise ETL/ELT pipelines across trading, alpha research, risk management, accounting and more.
  • Create and own golden source datasets (security master, account master, price master) that everything else downstream relies on.
  • Develop shared Python libraries for data APIs, logging and core data services, improving developer productivity across the firm.
  • Ensure high data quality, observability and governance using modern tooling and best practices.
  • Optimise large‑scale data processing workflows for performance, reliability and cost efficiency.
  • Partner with technical and non‑technical stakeholders to understand requirements and ship pragmatic, well‑communicated solutions.
  • Troubleshoot and support data pipelines, APIs and database performance issues in production.
What we’re looking for
  • 6+ years of software development experience, including 2+ years focused on data engineering.
  • Strong Python and SQL, with extensive hands‑on ETL/ELT pipeline design and automation experience.
  • Solid foundations in data structures, data modelling, query design and performance tuning in SQL databases (e.g. Postgres, MS SQL Server).
  • Experience with containerisation and deployment (Docker, Kubernetes).
  • Familiarity with modern data transformation and governance/observability tools.
  • Excellent communication skills and the ability to collaborate across quant, trading, risk and engineering teams.
Nice to have
  • Experience with modern cloud data platforms (e.g. Snowflake, Databricks or similar).
  • Financial markets literacy across asset classes (equities, fixed income, futures, options).
  • Experience with data observability tools (e.g. OpenMetadata, Great Expectations).
  • Dashboarding/BI experience and/or Python web APIs (e.g. FastAPI).
  • Exposure to distributed processing frameworks such as Dask or Spark.
Location & Working model

This role is based in New York, operating on a hybrid model of four days per week in the office with one day remote. You’ll join a lean, senior team with an owner’s mindset, where smart risk‑taking, collaboration, humility and integrity are genuinely part of how decisions get made.

If you’re a Data Engineer who enjoys owning mission‑critical pipelines, working close to the investment decision‑making process and shaping a modern data platform rather than just inheriting one, we’d like to hear from you. Apply here or reach out directly for a confidential conversation.

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