Senior Data Streaming Engineer (Apache Flink & Apache Spark)

We are looking for a highly skilled Senior Data Streaming Engineer with strong expertise in Apache Flink and Apache Spark to design, build, and optimize enterprise-grade real-time and batch data processing solutions. The ideal candidate will have extensive experience developing streaming applications, event-driven architectures, and high-performance ETL pipelines while ensuring scalability, reliability, and low-latency processing. Responsibilities - Design, develop, and maintain scalable real-time data processing pipelines. - Build streaming applications using Apache Flink DataStream API, Table API, and Spark Structured Streaming. - Develop batch and near real-time ETL workflows. - Implement stateful stream processing, event-time processing, watermarking, windowing, checkpointing, and fault-tolerant streaming solutions. - Optimize Spark and Flink jobs for performance, scalability, and resource utilization. - Process large-scale datasets with high throughput and low latency. - Collaborate with architects, data engineers, and business teams to deliver enterprise data solutions. - Implement monitoring, logging, alerting, and troubleshooting mechanisms. - Ensure data quality, governance, and security best practices. Required Skills - 8–10 years of Data Engineering experience. - Strong hands-on expertise in Apache Flink: - DataStream API - Table API - SQL API - Stateful Stream Processing - Event-Time Processing - Windowing - Watermarks - Checkpointing - Fault Tolerance - Strong expertise in Apache Spark: - Spark Core - Spark SQL - Structured Streaming - Experience developing high-volume ETL pipelines. - Strong understanding of distributed computing concepts. - Experience with performance tuning and optimization. - Good programming skills in Java, Scala, or Python. Preferred Skills - Kafka or Azure Event Hubs - Azure, AWS, or GCP - Docker & Kubernetes - CI/CD implementation - Data Lakes - Microservices Architecture - Agile development