Jefferies
Senior Data Engineer - Reference Data (Assistant Vice President)
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Senior Data Engineer – Reference Data Group
Jefferies Financial Technology Division
Jefferies is searching for a highly experienced Senior Data Engineer to join the Reference Data Group within our Technology division. You will play a key role in designing, building, and managing the firm's critical reference data platforms—including Security Master, Account Master, and Counterparty Master—which underpin trading, risk, compliance, and operations globally.
The Opportunity
This is a high-impact, hands-on engineering role where you’ll collaborate with business stakeholders and cross-functional teams to deliver scalable, robust, and well-governed data pipelines and platforms on modern cloud infrastructure. Reference Data at Jefferies is foundational—the data you work with powers trading systems, regulatory reporting, risk models, and client-facing applications globally.
(About The Team)
The Reference Data Group is responsible for maintaining authoritative master data for securities, accounts, and counterparties across the firm. The team manages end-to-end data ingestion from vendors and internal systems, normalization, golden record creation, and distribution to downstream consumers. The group operates on a cloud-native stack using Snowflake, AWS, and Apache Airflow, following engineering best practices such as CI/CD, code reviews, and automated testing.
Key Responsibilities
- Design, build, and maintain scalable data pipelines for Security Master, Account Master, and Counterparty Master using Python and Apache Airflow.
- Develop and optimize complex data transformations, stored procedures, and views in Snowflake, ensuring high performance and data quality.
- Own the entire data lifecycle—from source ingestion and normalization to golden record creation and downstream distribution.
- Collaborate with data consumers (trading, risk, compliance, operations) to understand requirements and deliver reliable data products.
- Build and maintain infrastructure-as-code and deployment pipelines using AWS, Git, and CI/CD tooling.
- Implement data quality frameworks, lineage tracking, and monitoring to ensure accuracy, completeness, and timeliness.
- Participate in design and code reviews, contribute to engineering standards, and mentor junior engineers.
- Work with external data providers (e.g., Bloomberg, Refinitiv) to onboard and manage data feeds.
- Contribute to platform modernization and promote best practices across the team.
- Troubleshoot production data issues, perform root cause analysis, and implement preventative measures.
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Required Skills & Experience
Core Requirements
- 7+ years of hands-on data engineering experience
- Expert-level Python for data engineering and automation
- Strong Snowflake experience:
- Proficiency in SQL, stored procedures, streams, tasks, and performance tuning
- Production experience with Apache Airflow:
- DAG design, scheduling, dependency management
- Solid AWS cloud experience:
- S3, Lambda, Glue, IAM, or equivalent services
- Git proficiency including branching, pull requests, and code reviews
- CI/CD pipeline experience (GitHub Actions, Jenkins, or similar)
- Strong understanding of data modeling (dimensional, relational, hub-spoke patterns)
- Experience building and scaling production-grade data pipelines
Preferred (Financial Services Experience)
- Financial services experience (Preferred but not mandatory).
- Strong candidates from other industries with relevant data engineering expertise and a willingness to learn financial concepts are encouraged.
Nice-to-Have Experience
- Financial reference data experience (Security Master, Counterparty, Account)
- Knowledge of financial instruments (equities, fixed income, derivatives, FX)
- Familiarity with data vendors (Bloomberg, Refinitiv, FactSet)
- Data governance, lineage tools, or metadata management experience
- Experience with dbt or transformation frameworks
- Exposure to Kafka or event-driven architectures
- Background in regulated financial services environments
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Core Competencies
- Communication: Ability to articulate complex technical concepts to non-technical stakeholders (business analysts, traders, senior management).
- Collaboration: A strong team player who works effectively across engineering, business, and operations.
- Problem Solving:
- Analytical mindset with a track record of resolving data quality and pipeline issues in production.
- Ownership:
- Takes full accountability for data products from design through monitoring and improvement.
- Adaptability:
- Manages multiple priorities in a dynamic financial services environment.
What We Offer
- Opportunity to work on firm-critical, high-visibility data infrastructure supporting global trading and operations.
- Engineering-driven culture with emphasis on code quality, testing, and continuous improvement.
- Access to modern cloud tools and influence over platform architecture decisions.
- Exposure to a diverse range of financial products and business domains as a leading global investment bank.
About Jefferies
Jefferies is a leading global, full-service investment banking and capital markets firm, providing:
- Advisory, sales and trading, research, and wealth & asset management services
- Over 40 offices worldwide
Our Commitments
Values-Driven Culture: We believe in diversity, creativity, and innovation, fostering a workforce that reflects the communities we serve.
Equal Opportunity Employer: Jefferies is committed to affirmative action and ensuring all qualified applicants receive fair consideration without regard to:
- Race, religion, color, national origin, ancestry
- Gender, sexual orientation, pregnancy
- Age, disability, veteran status
- Genetic information, reproductive health, or other protected statuses
We provide reasonable accommodations for individuals with disabilities.
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