Kafka Developer - PwC-Madhusudana

Kafka Developer SeniorAssociate (7 10 Years) Our Analytics & Insights Managed Services team brings a unique combination of industry expertise, technology, data management and managed services experience to create sustained outcomes for our clients and improve business performance. We empower companies to transform their approach to analytics and insights while building your skills in exciting new directions. Have a voice at our table to help design, build, and operate the next generation of data and analytics solutions as an Associate. Job Requirements and Preferences Basic Qualifications Minimum Degree Required: Bachelor s Degree in Engineering, Statistics, Mathematics, Computer Science, Data Science, Economics, or a related quantitative field Minimum Years of Experience: 3 5 years of professional experience in analytics, data science, or business intelligence roles Preferred Qualifications Degree Preferred: Master s Degree in Engineering, Statistics, Data Science, Business Analytics, Economics, or related discipline Preferred Fields of Study: Data Analytics/Science, Statistics, Management Information Systems, Economics, Computer Science Preferred Knowledge & Skills As a Senior Associate in Data Engineering , you ll design and optimize scalable data pipelines, streaming solutions, and data models across enterprise platforms. You ll work with Kafka for real-time streaming, leverage Dataiku and Spark on Cloudera for advanced data workflows, and use Python/PySpark and SQL for data transformations. You ll also mentor junior engineers, enforce best practices, and collaborate with architects and business stakeholders to ensure robust, efficient, and scalable solutions: Data Streaming & Real-Time Processing (Kafka) Design and implement streaming data ingestion pipelines using Kafka producers, consumers, and topics Manage partitions, consumer groups, offsets, and retention strategies for scalability and fault tolerance Integrate Kafka with downstream platforms such as Spark, Cloudera, or Snowflake Implement monitoring, error handling, and recovery strategies for streaming workloads Data Engineering with Dataiku & Spark (Cloudera) Build and optimize ETL/ELT workflows in Dataiku and Spark on Cloudera Develop reusable and modular data pipelines for batch and near real-time workloads Optimize Spark jobs using partitioning, broadcast joins, and caching for large-scale datasets Collaborate with platform teams to ensure efficient execution on Cloudera clusters Python & PySpark Development Write scalable Python/PySpark scripts for data cleansing, transformation, and enrichment Create reusable frameworks and libraries to accelerate development across teams Lead debugging sessions Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.