Job Overview

Citi is hiring a Senior Data Platform Engineer - Vice President in Pune, Maharashtra, with a hybrid work model. This is a senior technical leadership opportunity within the Fixed Income Data Platform team. The role focuses on building and improving high-performance data platforms that support demanding analytical and trading environments.

The successful candidate will combine deep software engineering skills with architecture leadership and hands-on development. The position involves designing low-latency streaming systems, scalable data pipelines, microservices, distributed infrastructure, and resilient platform services. You will also coach engineers, review architecture and code, evaluate emerging open-source technologies, and help establish strong engineering practices.

This is an experienced professional role rather than a purely managerial position. Candidates are expected to remain technically engaged, contribute code, solve complex platform problems, and influence long-term technical direction.

Key Responsibilities

• Lead technical design and implementation of scalable, fault-tolerant data pipelines, streaming platforms, and microservices.
• Contribute directly to software development, architecture reviews, code reviews, testing, and technical problem solving.
• Provide hands-on technical coaching to junior and mid-level data engineers across multiple technology stacks.
• Design and operate real-time streaming solutions using Apache Flink and related data engineering technologies.
• Work with Flink infrastructure, clusters, state management, Flink SQL, and DataStream API capabilities.
• Design, maintain, enhance, and migrate high-performance Redis infrastructure for mission-critical workloads.
• Evaluate emerging open-source data and streaming technologies and help integrate suitable technologies into the platform.
• Improve platform performance, availability, resilience, scalability, and operational efficiency.
• Work with distributed data systems and low-latency storage or query technologies to support large-scale data pipelines.
• Collaborate with engineering, data science, and business stakeholders to turn complex requirements into reliable technical solutions.
• Support cloud-native deployment and operation of microservices, streaming components, and data services.
• Drive secure and reliable delivery through CI/CD, Agile development, code quality standards, and automated testing.
• Investigate difficult technical incidents and act as an escalation point for complex platform issues.
• Contribute to migration, infrastructure planning, operational improvements, and long-term technical strategy.
• Participate in on-call or non-standard support activities when required for critical platform operations.

Required Skills

The ideal candidate should have strong software engineering fundamentals and extensive experience building systems in data-intensive environments. You should be comfortable working across multiple programming languages and technologies rather than being limited to one development stack.

Strong architectural knowledge is required for microservices, distributed systems, real-time data processing, streaming pipelines, scalability, resilience, and low-latency application design. The role also requires practical experience with infrastructure operations and cloud-native engineering.

Hands-on Java experience is important, with Java 11 or later preferred. Strong Python experience is also required. Familiarity with modern front-end technologies such as Angular or React is useful for working across broader application environments.

Apache Flink expertise is a major requirement. Candidates should understand real-time stream processing, Flink SQL, DataStream API, state management, infrastructure setup, cluster operations, enhancement, and migration strategies.

Redis knowledge should extend beyond basic caching. The role requires practical understanding of Redis data structures, caching patterns, publish/subscribe mechanisms, cluster operations, maintenance, enhancement, and migration for high-performance systems.

Required Technologies

• Java 11+
• Python
• Apache Flink
• Flink SQL
• Flink DataStream API
• Redis
• Apache Kafka
• Microservices
• Distributed Systems
• Data Pipelines
• Angular
• React
• Trino
• Pinot
• Druid
• Ignite
• Kubernetes
• OpenShift
• ECS
• Jenkins
• TeamCity
• SonarQube
• Git
• CI/CD
• Agile
• SDLC
• Unit Testing
• Integration Testing
• Redis Pub/Sub
• Redis Clusters

Preferred Skills

Experience with Large Language Models is an additional advantage. Candidates with practical exposure to LLM integration, prompt engineering, or fine-tuning can bring useful complementary skills to the role.

Experience evaluating open-source streaming frameworks, caching technologies, and large-scale data platforms is also valuable. Familiarity with cloud-native application operations and container orchestration using Kubernetes, OpenShift, or ECS will strengthen an application.

Strong knowledge of engineering quality practices, architectural patterns, coding standards, automated testing, continuous integration, and secure deployment is expected.

Education

A Bachelor’s degree or university degree is required, or equivalent experience may be considered according to the supplied job information.

Experience

The role requires at least 10 years of demonstrable, hands-on software development experience. Within that background, candidates should have approximately 3 to 5 years in a lead technical contributor or staff engineer position in a data-intensive environment.

Applicants should be able to demonstrate substantial experience designing and implementing data platforms, distributed systems, streaming architectures, microservices, and cloud-native applications. The position also requires the ability to provide technical direction and coach other engineers while continuing to contribute directly to engineering work.

Soft Skills

Strong technical communication is essential. You should be able to explain architecture decisions and complex engineering concepts to developers, technical leaders, data scientists, and business stakeholders.

The role also requires coaching ability, collaboration, ownership, analytical thinking, structured problem solving, and sound technical judgment. A data-driven approach to decision making and the ability to balance immediate engineering needs with longer-term platform strategy are important for success.

Benefits of Working in this Role

This role provides an opportunity to work on highly scalable data platforms supporting demanding financial technology use cases. It combines hands-on engineering, architecture, distributed systems, real-time streaming, cloud-native technologies, and technical leadership.

The position also offers exposure to open-source technology evaluation, large-scale platform engineering, data-intensive systems, and emerging areas such as LLM integration. The leadership scope includes direct technical coaching and participation in major platform decisions.

Work Mode

This is a hybrid role based in Pune, Maharashtra, India. The supplied job description also notes that occasional non-standard shifts, nights, weekends, or on-call responsibilities may be required to support critical platform operations.

Location

The job is based in Pune, Maharashtra, India.

Who Should Apply

This opportunity is suitable for experienced data platform engineers, staff engineers, lead engineers, and senior software engineers with a strong background in distributed systems and real-time data engineering.

Candidates should highlight experience with Apache Flink, Redis, Kafka, microservices, Java, Python, cloud-native infrastructure, Kubernetes or related platforms, and CI/CD. Professionals who have designed low-latency systems or operated mission-critical streaming and data platforms should clearly describe those accomplishments.

Career Growth

A Vice President-level technical engineering role can provide a pathway toward staff engineering, principal engineering, data platform architecture, technology leadership, or broader engineering strategy positions. Building expertise across streaming, distributed systems, cloud-native architecture, and technical coaching can strengthen long-term leadership opportunities in data engineering and financial technology.

Application Advice

Tailor your resume to demonstrate hands-on engineering impact rather than listing technologies without context. Clearly state your total software development experience and the duration of your lead or staff-level technical responsibilities.

Highlight projects involving Apache Flink, Redis, Kafka, microservices, low-latency pipelines, distributed systems, Kubernetes, OpenShift, ECS, and cloud-native applications. Include measurable examples of performance improvements, resilience enhancements, platform migrations, cost or operational improvements, CI/CD modernization, and production problem resolution where available.

Also mention experience with Jenkins, TeamCity, SonarQube, Git, Agile delivery, automated testing, and technical coaching. If you have worked with LLMs, prompt engineering, or model fine-tuning, include those skills as additional strengths.