Role Description

Responsibilities Develop and maintain real-time data pipelines using Apache Kafka (MSK or Confluent) and AWS services.

Configure and manage Kafka connectors, ensuring seamless data flow and integration across systems.

Demonstrate a strong understanding of the Kafka ecosystem, including producers, consumers, brokers, topics, and schema registry.

Design and implement scalable ETL/ELT workflows to process large volumes of data efficiently.

Optimize data lake and data warehouse solutions using AWS services such as Lambda, S3, and Glue.

Implement robust monitoring, testing, and observability practices to ensure data platform reliability and performance.

Uphold data security, governance, and compliance standards across all data operations.





Requirements Minimum of 5 years of experience in data engineering or related roles.

Proven expertise with Apache Kafka and the AWS data stack (MSK, Glue, Lambda, S3, etc.).

Proficient in coding with Python, SQL, and Java (Java strongly preferred). Person needs to adaptable to write code in Python/Java Experience with infrastructure-as-code tools (e.g. CloudFormation) and CI/CD pipelines.

Excellent problem-solving skills and strong communication and collaboration abilities.

Skills

Python, SQL, AWS CloudFormation, CI/CD

📌 Lead II - Data Engineering (Pune)
🏢 UST
📍 Pune