Data Engineer
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* Own end-to-end data workflows that move, transform, and surface pricing, security, and reference information across the firm.
* Connect third-party data feeds from major financial information providers and standardize output for consumption by investment teams.
* Translate raw vendor datasets into a unified internal schema covering equities, rates, credit, FX, commodities, and digital assets.
* Work closely with investment and research staff to understand data needs and deliver timely, accurate solutions.
* Run and tune cloud-based storage and compute resources; keep costs and performance balanced as usage scales.
* Own operational stability of the data platform — triage issues, enforce alerting, and meet uptime commitments.
* Establish and enforce checks that catch data problems before they reach downstream consumers.
* Assess current tooling and spend; surface opportunities to do more with less across infrastructure and subscriptions. REQUIREMENTS
* Degree in a technical or quantitative field; Computer Science, Mathematics, or Engineering preferred.
* At least 5+ years working directly with financial data in an institutional investment or capital markets setting.
* Practical knowledge of one or more major financial data platforms ( Bloomberg, ICE, or Refinitiv ), including feed formats and delivery mechanisms.
* Fluent in Python and SQL; comfortable owning pipeline code in a production environment, not just prototyping.
* AWS hands-on experience required; familiarity with serverless compute, columnar storage, and managed relational databases expected.
* Solid grasp of how financial instruments are structured and identified across asset classes and data vendors.
* Experience scheduling and orchestrating multi-step data workflows using a modern workflow tool.
* Working knowledge of what good data looks like, able to define rules, catch anomalies, and trace issues to source.
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