Java/Python & Flink/Redis Application Development Analyst

Citi · Pune · 4+ yrs experience · Posted 2026-07-18

Tech stack: Angular, Java, Jenkins, Kafka, Kubernetes, Python, React, Redis, SQL

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About the role

Fixed 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. FI’s activities include origination, structuring, investing, lending, and market making and it offers a variety of products including, but not limited to, corporate bonds, emerging markets bonds, asset backed securities, mortgage backed securities, collateralized loan obligations (CLOs), municipal securities, agency securities, short term interest rate products, loans, letters of credit, and derivative instruments.
Responsibilities: - Analyzes complex system requirements, including identifying program interactions and appropriate interfaces between impacted components and sub-systems within microservices architectures and distributed data pipelines
- Participate actively in Sprint Planning, Tasking, and Estimation of assigned work for the platform, demonstrating a clear understanding of cross-stack dependencies.
- Contribute to component and service design for analytical and streaming services considering scalability and performance across varied technologies.
- Work on bug resolution and application improvements, with a strong focus on performance, maintainability, and code quality in streaming and microservices environments
- Contribute to the strategic planning, setup, and maintenance of Flink and Redis infrastructure, including evaluating new streaming frameworks and caching solutions.
- Flexibly contribute across the full stack, adapting to diverse programming languages and frameworks as project needs evolve.
- May occasionally work a non-standard shift including nights and/or weekends and/or have on-call responsibilities.
- Stay abreast with new trends in open-source tooling and champion innovative solutions that could help improve the efficiency of the Fixed Income platform community.
- Work closely with business stakeholders to help them leverage platform capabilities and develop efficient analytical tools.
- Continuously seek to automate manual touchpoints in the technology delivery pipeline.
- Recommended Qualifications: 4+ years of demonstrable and relevant experience in software development, with a strong emphasis on designing and implementing Microservices and complex streaming/data pipeline architectures.
- Proven proficiency in at least two of the following core languages/frameworks: Java (strong focus), Python, Angular, React.
- Deep expertise and hands-on experience with Apache Flink for real-time stream processing, including Flink SQL, DataStream API, state management, and comprehensive knowledge of Flink infrastructure setup, maintenance, enhancement, and migration strategies.
- Experience in evaluating and integrating alternative streaming frameworks is highly valued.
- In-depth knowledge and practical experience with Redis, encompassing not only data structures, caching patterns, and pub/sub mechanisms but also expertise in Redis cluster setup, maintenance, enhancement, and migration strategies for high-performance applications.
- Extensive hands-on experience with Microservices architecture design patterns, and deployment strategies.
Qualifications: - with Large Language Models (LLMs), including fine-tuning, prompt engineering, and integrating LLMs into applications, is a plus.
- 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 distributed data pipelines with the design and implementation of cloud-native applications and deployment via Kubernetes / OpenShift, specifically for managing microservices and streaming data services
- Good understanding of data modeling, partitioning, and sharding of huge data sets for optimal performance in large-scale, distributed data platforms Software Engineering Skills: working on a Continuous Integration and Continuous Delivery (CI/CD) environment, with a strong focus on rapid and reliable deployment of microservices and streaming components and data access layers.
- Familiarity with TeamCity, SonarQube, and Jenkins.
- with the SDLC lifecycle and in working within an Agile environment, adapting to fast-paced data requirements.
- Demonstrable understanding and experience of engineering best practices: design patterns, coding standards, code review, and robust unit/integration testing across various languages.
- Strong experience with standard CI tools (Jenkins, TeamCity, SonarQube, Git).
- Bachelor’s degree/University degree or equivalent experience.

Qualifications

- with Large Language Models (LLMs), including fine-tuning, prompt engineering, and integrating LLMs into applications, is a plus.
- 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 distributed data pipelines with the design and implementation of cloud-native applications and deployment via Kubernetes / OpenShift, specifically for managing microservices and streaming data services
- Good understanding of data modeling, partitioning, and sharding of huge data sets for optimal performance in large-scale, distributed data platforms Software Engineering Skills: working on a Continuous Integration and Continuous Delivery (CI/CD) environment, with a strong focus on rapid and reliable deployment of microservices and streaming components and data access layers.
- Familiarity with TeamCity, SonarQube, and Jenkins.
- with the SDLC lifecycle and in working within an Agile environment, adapting to fast-paced data requirements.
- Demonstrable understanding and experience of engineering best practices: design patterns, coding standards, code review, and robust unit/integration testing across various languages.
- Strong experience with standard CI tools (Jenkins, TeamCity, SonarQube, Git).
- Bachelor’s degree/University degree or equivalent experience.

Responsibilities

- Analyzes complex system requirements, including identifying program interactions and appropriate interfaces between impacted components and sub-systems within microservices architectures and distributed data pipelines
- Participate actively in Sprint Planning, Tasking, and Estimation of assigned work for the platform, demonstrating a clear understanding of cross-stack dependencies.
- Contribute to component and service design for analytical and streaming services considering scalability and performance across varied technologies.
- Work on bug resolution and application improvements, with a strong focus on performance, maintainability, and code quality in streaming and microservices environments
- Contribute to the strategic planning, setup, and maintenance of Flink and Redis infrastructure, including evaluating new streaming frameworks and caching solutions.
- Flexibly contribute across the full stack, adapting to diverse programming languages and frameworks as project needs evolve.
- May occasionally work a non-standard shift including nights and/or weekends and/or have on-call responsibilities.
- Stay abreast with new trends in open-source tooling and champion innovative solutions that could help improve the efficiency of the Fixed Income platform community.
- Work closely with business stakeholders to help them leverage platform capabilities and develop efficient analytical tools.
- Continuously seek to automate manual touchpoints in the technology delivery pipeline.
- Recommended Qualifications: 4+ years of demonstrable and relevant experience in software development, with a strong emphasis on designing and implementing Microservices and complex streaming/data pipeline architectures.
- Proven proficiency in at least two of the following core languages/frameworks: Java (strong focus), Python, Angular, React.
- Deep expertise and hands-on experience with Apache Flink for real-time stream processing, including Flink SQL, DataStream API, state management, and comprehensive knowledge of Flink infrastructure setup, maintenance, enhancement, and migration strategies.
- Experience in evaluating and integrating alternative streaming frameworks is highly valued.
- In-depth knowledge and practical experience with Redis, encompassing not only data structures, caching patterns, and pub/sub mechanisms but also expertise in Redis cluster setup, maintenance, enhancement, and migration strategies for high-performance applications.
- Extensive hands-on experience with Microservices architecture design patterns, and deployment strategies.

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