Job
Description
This role will be instrumental in building and maintaining robust, scalable, and reliable data pipelines using Confluent Kafka, ksqlDB, Kafka Connect, and Apache Flink. The ideal candidate will have a strong understanding of data streaming concepts, experience with real-time data processing, and a passion for building high-performance data solutions. This role requires excellent analytical skills, attention to detail, and the ability to work collaboratively in a fast-paced environment. Essential Responsibilities Design & develop data pipelines for real time and batch data ingestion and processing using Confluent Kafka, ksqlDB, Kafka Connect, and Apache Flink. Build and configure Kafka Connectors to ingest data from various sources (databases, APIs, message queues, etc.) into Kafka. Develop Flink applications for complex event processing, stream enrichment, and real-time analytics. Develop and optimize ksqlDB queries for real-time data transformations, aggregations, and filtering. Implement data quality checks and monitoring to ensure data accuracy and reliability throughout the pipeline. Monitor and troubleshoot data pipeline performance, identify bottlenecks, and implement optimizations. Automate data pipeline deployment, monitoring, and maintenance tasks. Stay up-to-date with the latest advancements in data streaming technologies and best practices. Contribute to the development of data engineering standards and best practices within the organization. Participate in code reviews and contribute to a collaborative and supportive team environment. Work closely with other architects and tech leads in India & US and create POCs and MVPs Provide regular updates on the tasks, status and risks to project manager The experience we are looking to add to our team Required Bachelors degree or higher from a reputed university 8 to 10 years total experience with majority of that experience related to ETL/ELT, big data, Kafka etc. Proficiency in developing Flink applications for stream processing and real-time analytics. Strong understanding of data streaming concepts and architectures. Extensive experience with Confluent Kafka, including Kafka Brokers, Producers, Consumers, and Schema Registry. Hands-on experience with ksqlDB for real-time data transformations and stream processing. Experience with Kafka Connect and building custom connectors. Extensive experience in implementing large scale data ingestion and curation solutions Good hands on experience in big data technology stack with any cloud platform - Excellent problemsolving, analytical, and communication skills. Ability to work independently and as part of a team Good to have Experience in Google Cloud Healthcare industry experience Experience in Agile Show more Show less
