Data Engineer

Wall Street Careers®; New York (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

Wall Street Careers is seeking a Senior Data Engineer to own end-to-end data workflows that support pricing, security and reference data across the firm.

You will connect feeds from Bloomberg, ICE or Refinitiv, translate vendor data into a unified schema across assets, and ensure production pipelines run reliably on AWS.

The role requires 5+ years in financial data, Python/SQL fluency, and a track record of maintaining scalable, cost-effective data infrastructure.

Qualifications

• Degree in a technical or quantitative field; Computer Science, Mathematics, or Engineering preferred.
• 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.

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.

Skills

Python

SQL

AWS

Data pipelines

Education

Bachelor's degree in Computer Science, Mathematics or Engineering

Tools

Bloomberg

ICE

Refinitiv

Job description

Global Asset Manager with over $50B of AUM.

JOB TITLE

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.