Apache Flink_5+ years

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