We are looking for a highly skilled Senior Data Streaming Engineer with solid 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

📌 Senior Data Streaming Engineer (Apache Flink & Apache Spark) (Madhavaram)
🏢 Nameless
📍 Madhavaram