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Job Overview
Job DescriptionFixed Income (FI) is the primary source of capital for corporations, governments, and nonprofits, providing liquidity and innovative solutions globally across the credit, municipal, and securitized markets. The Fixed Income Data Platform Team is the foundational pillar of this mission, engineered to provide the low latency, high concurrency, scalability, and unparalleled availability required for our groundbreaking solutions. Our Data Platform Engineering team operates at the forefront of innovation, constantly researching, adapting, and strategically deploying the latest open-source data platforms to meet Citi's unique and evolving needs. We are a collaborative, high-performing group dedicated to solving complex technical challenges and building highly performant, resilient systems.
We are seeking a Vice President, Lead Data Platform Engineer to provide deep technical expertise, hands-on contribution, and direct coaching to our talented engineering team. This role is pivotal in driving the technical design, development, and implementation of Citi's next-generation data platform, with a critical focus on architecting complex streaming solutions, robust data pipeline architectures, and scalable microservices. This platform empowers quantitative scientists and traders to rapidly iterate on and deploy cutting-edge analytical and trading tools. We are looking for a polyglot expert who can directly contribute across diverse technology stacks, guide technical direction, and elevate the skills of junior engineers through direct technical leadership.
Key Responsibilities:
Hands-on Technical Leadership & Coaching: Provide technical leadership through direct code contribution, architecture review, and hands-on guidance to junior and mid-level data engineers, fostering a culture of technical excellence and continuous learning across polyglot environments.
Drive & Implement Architecture & Design: Directly contribute to and drive the technical design and hands-on development of highly scalable, low-latency, fault-tolerant data pipelines, real-time streaming platforms (e.g., Flink), and microservices architectures.
Platform Infrastructure & Operations Deep Dive: Actively participate in the strategic planning, setup, enhancement, migration, and operational excellence of critical platform infrastructure, including distributed streaming (Flink) and high-performance caching solutions (Redis).
Open Source & Emerging Technologies Evaluation: Continuously research, evaluate, and prototype emerging open-source data and streaming technologies, leading their integration into Citi's data platform through direct implementation. This includes evaluating new streaming frameworks and caching solutions.
Performance & Resilience Optimization: Proactively identify and implement architectural and systemic performance optimizations to ensure optimal efficiency, responsiveness, and resilience across the entire data platform, including Flink and Redis clusters.
Cross-Functional Technical Collaboration: Collaborate closely with senior technical stakeholders across engineering, data science, and business teams to translate complex technical requirements into robust, high-impact implementations.
Delivery & Code Quality Assurance: Drive the timely, high-quality, and secure delivery of data platform features, championing agile methodologies, engineering best practices, and ensuring accountability for code quality and robust testing.
Technical Problem Solving: Act as a primary escalation point for complex technical challenges, providing expert diagnosis and hands-on resolution.
Operational Flexibility: May occasionally work a non-standard shift including nights and/or weekends and/or have on-call responsibilities to support critical platform operations.
Qualifications:
10+ years of demonstrable and highly hands-on experience in software development, with at least 3-5 years in a lead technical contributor or staff engineer role within a data-intensive environment.
Deep Architectural & Implementation Expertise: Proven expertise in designing, building, and implementing Microservices and complex streaming/data pipeline architectures.
Polyglot Proficiency & Technical Authority: Demonstrated ability to be a technical authority and actively contribute across multiple programming languages/frameworks, with strong hands-on experience in Java (Java 11+ preferred), and significant expertise in Python, along with practical knowledge of front-end technologies like Angular/React.
Expertise in Flink Ecosystem: In-depth architectural understanding and hands-on experience with Apache Flink for real-time stream processing, including Flink SQL, DataStream API, and state management. Comprehensive knowledge of Flink infrastructure setup, maintenance, enhancement, migration strategies, and experience in evaluating/integrating alternative streaming frameworks.
Mastery of Redis: In-depth knowledge and practical experience with Redis, encompassing not only data structures, caching patterns, and pub/sub mechanisms but also strategic expertise in Redis cluster setup, maintenance, enhancement, and migration strategies for mission-critical, high-performance applications.
Distributed Systems & Data Engineering: Deep understanding of distributed systems concepts and extensive hands-on experience with data distribution platforms like Apache Kafka, and various big data storage/querying systems (e.g., Trino, Pinot, Druid, Ignite) for low-latency access in large-scale, distributed data pipelines.
Cloud-Native & DevOps Contribution: Proven experience with the design, implementation, and operational aspects of cloud-native applications and deployment via Kubernetes / OpenShift / ECS, specifically for managing microservices, streaming, and data services.
Technical Leadership, Coaching & Communication: Exceptional ability to provide technical direction, coach junior engineers through hands-on collaboration, and articulate complex technical concepts clearly to diverse audiences.
Advanced Problem Solving & Strategic Technical Thinking: Excellent problem-solving skills, a data-driven approach to technical decision-making, and the ability to define and execute long-term technical strategies through direct implementation.
Experience with Large Language Models (LLMs), including fine-tuning, prompt engineering, and integrating LLMs into applications, is a plus.
Software Engineering Excellence:
Demonstrable experience driving and implementing CI/CD strategies for rapid, reliable, and secure deployment of microservices and streaming components. Familiarity with TeamCity, SonarQube, and Jenkins.
Expertise in the SDLC lifecycle within an Agile environment, adapting to fast-paced data requirements and directly contributing to continuous process improvement.
A champion of engineering best practices: architectural patterns, coding standards, rigorous code review, and robust unit/integration testing across diverse technologies.
Strong experience with standard CI tools (Jenkins, TeamCity, SonarQube, Git).
Education:
Bachelor’s degree/University degree or equivalent experience
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Job Family Group:
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Job Family:
Applications Development------------------------------------------------------
Time Type:
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Most Relevant Skills
Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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