Lead Python and Spark Data Engineer - Vice President

Citi Futures and Derivatives Clearing Technology supports a rapidly growing business that uses technological innovation to maintain competitive advantage in a constantly evolving market. Working closely with the business, external vendors and internal technology teams, you would build-out and maintain our next generation clearing platforms. You would manage complex projects that will involve everything from incorporating a new functionality within the existing ecosystem, to analyzing new requirements, documenting solutions, managing implementation and testing systems, ensuring that they are fit for purpose. You would regularly work with a range of Business Analysts and high-profile stakeholders.

The Data and Reporting team develops and supports a platform that provides client reporting and feeds other downstream applications within Citi. It provides reporting such as real-time trades, positions, initial and variation margin, positions and balances for external clients and internal users such as traders, operations and sales. A major ongoing initiative is to modernize the existing platform in order to provide scale and to enhance product offerings and new business requirements.

As the development lead for the data and reporting, you will lead the team to deliver best in class technical solutions to meet the needs of our Futures and Clearing business. This includes researching best practices, designing the application and data and integration architecture, designing the solutions, and delivering our application to the business. The team works closely with cross-functional business users, QA engineers and BAs collaborating to deliver best in class solutions. This role suits experienced architects/developers who have excellent communication and are passionate about driving technical solutions through leadership, excellence, collaboration. Responsibilities:

Own a large-scale data warehouse; develop data products; and lead the architecture, design, development, and maintenance of scalable and secure data architectures to support downstream reporting applications, data integration, and simplified complex data processes — utilizing best engineering practices and data lifecycle management principles.

Identify, evaluate, implement improvements to legacy systems, ensure alignment with target architecture design

Provide strong leadership to engineering teams including mentoring, code review and enforcing engineering best practices.

Own and define data models, taxonomies, metadata, data mappings, data standards, versioning, and semantic layers for domains and data products and support data consumption, AI enablement, and regulatory requirements.

Build automated data integration solutions and data pipelines including reference data to meet business and reporting requirements

Exhibit strong leadership qualities, fostering a positive and collaborative work environment, providing guidance and mentorship to team members, and promoting a culture of continuous learning.

Implement data governance and management frameworks, quality standards, and data controls to ensure data accuracy and security, enabling downstream applications to consume data with confidence. Manage and maintain data process documentation

Define target-state data architecture and drive delivery against the strategy, manage the execution to delivery

Contribute to technical direction and enhancement as a technical expert in data development and implementation phases, providing in-depth and sophisticated analyses to define problems and develop innovative solutions

Work closely with business users, stakeholders, BAs, product managers and other development teams to understand problem space, brainstorm ideas, approaches, and solutions.

Contribute to CI/CD implementation using DevOps best practices and ensure robust testing framework is utilized for functional and nonfunctional testing for the release cycles based on industry and Citi standards and work to implement them.

Contribute to technical direction and strategic decisions as a technical expert in all development and implementation phases, providing in-depth and sophisticated analyses to define problems and develop innovative solutions

Demonstrate a data-driven approach to problem-solving and decision-making, utilizing metrics, and performance indicators to assess team efficiency and identify improvement opportunities.

Manage and maintain data processes and jobs. Partner with the Support team to ensure the stability of the production environment through proactive monitoring and health checks

Partner with other Citi development teams to build APIs, integrations and share components that are critical to our platform’s success.

Qualifications:

Strong experience in designing and building best in class enterprise data architecture with site engineering excellence in a highly matrixed, complex organization

Strong experience in architecting complex, end-to-end data pipelines within highly available, distributed systems — encompassing data extraction, ingestion, and processing of large-scale datasets

Strong hands-on, advanced development experience with very large databases, complex data models, stored procedures, error handling, performance tuning and profiling, data security, database optimization, and configurations

Strong experience in large complex physical and logical data model design and development for data warehouse, reporting and reference and master data.

Hands-on experience with complex data integration and developing scalable, high-volume data pipelines using APIs, Kafka, Python, Java, Airflow, and Spark

Proven experience in developing data quality and reconciliation controls, data lineage tracking, and data catalog documentation; establishing data control monitoring and proactively identifying and resolving data inconsistencies and gaps

Excellent verbal and written communication skills, enabling effective collaboration with cross-functional teams, stakeholders, and management.

Strong hands-on experience in S3, Starburst, Oracle database, Databricks and Snowflake preferred.

Strong hands-on experience with modern software paradigms including cloud-native (AWS, Docker) and microservices

Experience in implementation of DevOps such as CI/CD and modern best practises such as testing frameworks and the SOLID principles; CI/CD tooling, automation of testing tools

Passion and commitment for adopting new technologies with exploratory mind-set

Experience working in an Agile/Scrum work environment

Experience in building observability dashboard for data processes and job monitoring

Innovative ideas and can-do attitude to work under pressure

Experience in managing agile scrum teams and end-to-end delivery

Strong understanding of trading data and experience working within the financial services industry is required

Experience in GenAI/Agentic, AI workflow, AI governance, AI agent, and MCPs automation development

Education:

Bachelor’s degree/University degree or equivalent experience in computer sciences, engineering, math/statistics

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

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