Data Engineer

<p><strong>COMPANY</strong></p><p>Global Asset Manager with over $50B of AUM.</p><p><br /></p><p><strong>JOB TITLE</strong></p><p>Data Engineer</p><p><br /></p><p><strong>RESPONSIBILITIES</strong></p><ul><li>Own end-to-end data workflows that move, transform, and surface pricing, security, and reference information across the firm.</li><li>Connect third-party data feeds from major financial information providers and standardize output for consumption by investment teams.</li><li>Translate raw vendor datasets into a unified internal schema covering equities, rates, credit, FX, commodities, and digital assets.</li><li>Work closely with investment and research staff to understand data needs and deliver timely, accurate solutions.</li><li>Run and tune cloud-based storage and compute resources; keep costs and performance balanced as usage scales.</li><li>Own operational stability of the data platform — triage issues, enforce alerting, and meet uptime commitments.</li><li>Establish and enforce checks that catch data problems before they reach downstream consumers.</li><li>Assess current tooling and spend; surface opportunities to do more with less across infrastructure and subscriptions.</li></ul><p><br /></p><p><strong>REQUIREMENTS</strong></p><ul><li>Degree in a technical or quantitative field; Computer Science, Mathematics, or Engineering preferred.</li><li>At least 5+ years working directly with financial data in an institutional investment or capital markets setting.</li><li>Practical knowledge of one or more major financial data platforms ( Bloomberg, ICE, or Refinitiv ), including feed formats and delivery mechanisms.</li><li>Fluent in Python and SQL; comfortable owning pipeline code in a production environment, not just prototyping.</li><li>AWS hands-on experience required; familiarity with serverless compute, columnar storage, and managed relational databases expected.</li><li>Solid grasp of how financial instruments are structured and identified across asset classes and data vendors.</li><li>Experience scheduling and orchestrating multi-step data workflows using a modern workflow tool.</li><li>Working knowledge of what good data looks like, able to define rules, catch anomalies, and trace issues to source.</li></ul><p><br /></p>