Data Platform Engineer - Assistant Vice President

Citi · Pune · 5+ yrs experience · Posted 2026-07-18

Tech stack: AWS, Docker, GCP, Java, Kafka, Kubernetes, SQL

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About the role

We are seeking a talented and passionate engineer to join our growing team. As a key member of our data platform team, you will design, develop, and maintain a high-performance platform for streaming data pipeline and analytics using cutting-edge technologies. You will work closely with the Platform Lead Engineer and other team members to deliver innovative solutions that drive data-driven decision-making within the organization.
Responsibilities: - Design, develop, and maintain robust and scalable data platform using Java and related technologies (e.g., Apache Flink, Kafka, Trino).
- Advise data engineers on how to build and optimize real-time and batch data processing applications to support low-latency requirements.
- Extend the platform with data integration solutions between various data sources and targets, including databases, APIs, and streaming platforms.
- Contribute to the design and development of event-driven architectures.
- Write clean, well-documented, and testable code.
- Collaborate effectively with other engineers, product managers, and stakeholders throughout the software development lifecycle (SDLC), adhering to Agile methodologies.
- Stay up-to-date with the latest trends and technologies in the data engineering space.
Qualifications: - Bachelor’s degree in Computer Science, Engineering, or a related field.
- Minimum 5 years of experience developing and deploying production-ready Java applications in a data engineering context.
- Strong experience with core Java (version 11 or higher), SQL, and database APIs.
- Proven experience working with distributed stream processing frameworks like Apache Flink, Spark Streaming, or Kafka Streams.
- Experience with event-driven architectures and real-time data processing.
- Solid understanding of OOP concepts, multithreading, and thread pools.
- Familiarity with containerization technologies like Docker and deployment platforms like Openshift, ECS, or Kubernetes is a plus.
- Experience producing high quality code using agentic coding assistants
- Excellent communication and collaboration skills.
- Preferred Skills and Qualifications:
- Master’s degree in a relevant field.
- Contributions to open-source projects.
- Experience working in a cloud environment (AWS, GCP)

Qualifications

- Bachelor’s degree in Computer Science, Engineering, or a related field.
- Minimum 5 years of experience developing and deploying production-ready Java applications in a data engineering context.
- Strong experience with core Java (version 11 or higher), SQL, and database APIs.
- Proven experience working with distributed stream processing frameworks like Apache Flink, Spark Streaming, or Kafka Streams.
- Experience with event-driven architectures and real-time data processing.
- Solid understanding of OOP concepts, multithreading, and thread pools.
- Familiarity with containerization technologies like Docker and deployment platforms like Openshift, ECS, or Kubernetes is a plus.
- Experience producing high quality code using agentic coding assistants
- Excellent communication and collaboration skills.
- Preferred Skills and Qualifications:
- Master’s degree in a relevant field.
- Contributions to open-source projects.
- Experience working in a cloud environment (AWS, GCP)

Responsibilities

- Design, develop, and maintain robust and scalable data platform using Java and related technologies (e.g., Apache Flink, Kafka, Trino).
- Advise data engineers on how to build and optimize real-time and batch data processing applications to support low-latency requirements.
- Extend the platform with data integration solutions between various data sources and targets, including databases, APIs, and streaming platforms.
- Contribute to the design and development of event-driven architectures.
- Write clean, well-documented, and testable code.
- Collaborate effectively with other engineers, product managers, and stakeholders throughout the software development lifecycle (SDLC), adhering to Agile methodologies.
- Stay up-to-date with the latest trends and technologies in the data engineering space.

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