Senior Data Engineer

The Senior Data Engineer will play a pivotal role in architecting and implementing data solutions for Cantor Fitzgerald's Technology Markets division. This role demands a deep understanding of financial services data, particularly in Equities Trading and Broker-Dealer Operations, to drive data-driven decision-making and operational efficiency. The successful candidate will collaborate closely with CRM product owners and front-office stakeholders to translate complex business workflows into robust data structures, ensuring accurate revenue tracking and attribution across coverage teams and products. Responsibilities Architect and build ETL/ELT pipelines for CRM data migration, cleansing, and normalization, resolving entity conflicts across legacy systems. Define canonical data models for client hierarchies, account structures, and relationship ownership, ensuring consistency across business lines. Address entity resolution challenges, including duplicate client records and mismatched account IDs, for accurate data representation. Translate business workflows into data structures that reflect actual coverage team operations, collaborating closely with front-office stakeholders. Design and maintain revenue tracking data models, including trading commissions, advisory fees, and relationship-attributed P&L, ensuring accurate attribution. Build attribution logic to allocate revenue across coverage teams, products, client accounts, and booking entities, considering commission sharing and soft dollar arrangements. Ensure accurate reconciliation between front-office OMS/EMS data, finance ledgers, and CRM-reported metrics for management reporting. Standardize client master data across Equities and adjacent product lines, applying consistent hierarchy models and industry-standard identifiers. Partner with Compliance, Operations, and Front Office to maintain data governance standards and support downstream reporting and compliance. Qualifications Deep understanding of financial services data, particularly in Equities Trading, Broker-Dealer Operations, or Client/Account Management. Familiarity with trade lifecycle data, order management, execution, settlement, and data flow into downstream reporting and P&L systems. Working knowledge of client and account hierarchy models, legal entity structures, account types, and sub-accounts, and their mapping to coverage and revenue attribution. Understanding of sell-side revenue tracking and attribution, including commissions, advisory fees, and reconciliation challenges between front-office and finance systems. Familiarity with counterparty and client identifier standards, such as LEI, DTCC, and FIX protocol client IDs. 5-8 years of hands-on data engineering experience, with at least 3 years in financial services, and expertise in Python, Java, and SQL. Direct experience with Salesforce CRM, including data model, APIs, and integration patterns, and proven experience with data normalization and entity resolution. Comfortable working directly with stakeholders across Front Office, Finance, Compliance, and Operations, and able to drive independent deliverables in a fast-paced environment. Preferred: Hands-on experience with AI/ML tools for data workflow automation and self-service analytics, and exposure to Cloud data platforms and industry data standards. Experience with Fixed Income, Prime Brokerage, or multi-asset CRM data, and orchestration/transformation tools like dbt or Airflow, is an advantage. Job Info Job Identification 248333 Posting Date 05/01/2026, 08:57 AM Locations 110 East 59th Street, New York, NY, 10022, US #J-18808-Ljbffr