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.