Senior Data Engineer

Cantor Fitzgerald

United States

United States

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À propos

Job Title: Senior Data Engineer – Trading & Client /CRM Domains Location: NYC Firm Overview: Cantor Fitzgerald L.P., with over 16,000 employees, has been a leading global financial services firm at the forefront of financial and technological innovation since 1945. Cantor Fitzgerald & Co. is a preeminent investment bank serving more than 5,000 institutional clients around the world, recognized for its strengths in fixed income and equity capital markets, investment banking, SPAC underwriting, PIPE placements, commercial real estate, and for its global distribution platform. Capitalizing on the firm’s financial acumen and technology prowess, Cantor’s portfolio of businesses also includes Prime Brokerage, Asset Management, and other businesses and ventures. For 79 years, Cantor has consistently fueled the growth of original ideas, pioneered new markets, and provided superior service to clients. Cantor operates trading desks in every major financial center globally, with offices in over 30 locations around the world. As one of the few remaining private partnerships on Wall Street, Cantor has the distinct ability to focus on long-term value creation and solid relationship building. Our structure allows us to respond quickly to client needs, develop solutions that address complex challenges, avoid the limitations of bureaucracy, and attract talented individuals who are driven to succeed. About the Role We are seeking a Senior Data Engineer with deep domain expertise in financial services data — spanning Trading, Sales, Broker-Dealer operations, and Client/Account management — to join a high-impact initiative at the intersection of data engineering and capital markets. The near-term focus is a firm-wide CRM replacement and rationalization program, where you will lead hands-on engineering work across client data migration, revenue attribution modeling, and integration between front-office systems and the new CRM platform (Salesforce). As the program matures, the role will expand to broader data platforms across trading and client domains. This is a role for someone who understands how capital markets businesses work — not just how to move data between systems. You should be as comfortable discussing commission structures, account hierarchies, and trade lifecycle as you are writing production Python or designing a dbt model. Key Responsibilities CRM Data Engineering & Migration Architect and build ETL/ELT pipelines to migrate, cleanse, and normalize client and account data into Salesforce, resolving entity conflicts across fragmented legacy source systems Define and enforce canonical data models for client hierarchies, account structures, and relationship ownership across business lines Resolve entity resolution challenges: duplicate client records, mismatched account IDs, and inconsistent counterparty identifiers across source systems Collaborate with CRM product owners and front-office stakeholders to translate business workflows into data structures that reflect how coverage teams actually operate Revenue Data & Attribution Design and maintain revenue tracking data models spanning trading commissions, advisory fees, and relationship-attributed P&L Build attribution logic to correctly allocate revenue across coverage teams, products, client accounts, and booking entities — including commission sharing, soft dollar, and CSA arrangements where applicable Ensure accurate reconciliation between front-office OMS/EMS data, finance ledgers, and CRM-reported metrics Support management reporting datasets for coverage leadership and senior management Client & Account Data Normalization Standardize client master data across Equities and adjacent product lines, applying consistent hierarchy models from legal entity through account and sub-account levels Apply industry-standard identifier frameworks (LEI, DTCC counterparty IDs, FIX protocol client identifiers) to support downstream reporting, compliance, and cross-system reconciliation Partner with Compliance, Operations, and Front Office to ensure data governance standards are met and maintained Ongoing Data Platform Work (expanding scope beyond CRM) Develop, test, and deploy production-grade pipelines in Python, Java, and SQL, with transformation layers built on modern frameworks (dbt preferred) Build and maintain reusable, well-documented data models that can support multiple downstream consumers across the firm Instrument data quality checks, lineage tracking, and alerting across the data stack Support integration with visualization and reporting tools used by business stakeholders (Tableau, Power BI, or equivalent) Qualifications: Domain Knowledge
(weighted heavily) Deep understanding of financial services data in one or more of the following: Equities Trading, Broker-Dealer Operations, Institutional Sales, or Client/Account Management Familiarity with trade lifecycle data — order management, execution, settlement, and how that data flows from OMS/EMS into downstream reporting and P&L systems Working knowledge of client and account hierarchy models as used in institutional markets: legal entity structures, account types, sub-accounts, and how they map to coverage and revenue attribution Understanding of how sell-side revenue is tracked and attributed — commissions, advisory fees, and related structures — and the reconciliation challenges that arise between front-office and finance systems Familiarity with counterparty and client identifier standards: LEI, DTCC, FIX protocol client IDs, or similar Technical Skills 5–8 years of hands-on data engineering experience, with at least 3 years in financial services Expert proficiency in Python, Java, and SQL; ability to write production-quality, well-tested code Direct experience with Salesforce CRM — data model, APIs, and integration patterns Proven experience with data normalization, entity resolution, and master data management at scale Comfortable working directly with stakeholders across Front Office, Finance, Compliance, and Operations Ability to drive deliverables independently in a fast-paced, project-driven environment Preferred Qualifications Hands-on experience applying AI/ML tools to automate data workflows and deliver self-service analytics and dashboards to non-technical stakeholders Experience with Fixed Income, Prime Brokerage, or multi-asset CRM data Experience with orchestration/transformation tools (dbt, Airflow, or similar) Exposure to Cloud data platforms (AWS, Azure, or GCP) Knowledge of industry data standards such as LEI, DTCC counterparty IDs, or FIX protocol client identifiers Experience with Salesforce Financial Services Cloud (FSC) or other capital markets CRM configurations Educational Qualifications: Bachelor’s Degree required Salary:
$180,000 - $210,000 The actual base salary will be determined on an individualized basis considering a wide range of factors including, but not limited to, relevant skills, experience, education, and, where applicable, licenses or certifications held. In addition to base salary and a competitive benefits package (including health, vision, and dental insurance, paid time off and a 401(k) retirement), this position may be eligible for additional types of compensation including discretionary bonuses and other short- and long-term incentives (e.g., deferred cash, equity, etc.). We do not accept unsolicited resumes, candidate referrals, or outreach from third-party recruiters or staffing agencies. Any such submissions will be considered property of Cantor Fitzgerald and will not be eligible for any placement fee. Recruiters must have a signed agreement with our Talent Acquisition team and be invited to submit candidates for a specific role. Direct contact with hiring managers or employees is strictly prohibited.

United States

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