Data Engineer

Wall Street Careers®; New York (NY); On-site; USD 150,000 - 210,000; Full time

Job summary

Wall Street Careers® is seeking an Investment Data Engineer to own end-to-end data workflows for pricing, securities, and reference data across the firm.

You will connect third-party data feeds (Bloomberg/Refinitiv/ICE), translate vendor datasets into a unified schema, and work with investment teams to deliver timely, accurate solutions. Proficiency in Python, SQL, and AWS is required, with production experience and cloud cost awareness.

Qualifications

• 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 setting.
• Experience with major financial data platforms (Bloomberg, ICE, Refinitiv), including feed formats and delivery.
• Fluent in Python and SQL; production-grade pipeline code ownership.
• Hands-on AWS experience; familiarity with serverless compute, columnar storage, and managed databases.
• Knowledge of financial instruments across asset classes and data vendors.

Responsibilities

• 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 investment teams.
• Translate raw vendor datasets into a unified internal schema for equities, rates, credit, FX, commodities, and digital assets.
• Work with investment and research staff to understand data needs and deliver timely, accurate solutions.
• Operate cloud storage and compute resources; manage costs and performance as usage scales.
• Ensure data platform reliability; triage issues, enforce alerts, and meet uptime commitments.
• Establish checks to catch data problems before downstream consumption; surface opportunities to optimize tooling and spend.

Skills

Python

SQL

Data pipelines

AWS

Data quality

Financial data

Education

B.S. or M.S. in Computer Science/Engineering/Math

Tools

Bloomberg

Refinitiv

ICE

AWS

Snowflake

Airflow

Job description

COMPANY

Global Asset Manager with over $50B of AUM.

JOB TITLE

Investment Data Engineer

RESPONSIBILITIES

• 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.