Key Responsibilities
- Design and develop real-time data pipelines using Kafka, Spark, AWS Kinesis, and related technologies.
- Build and support scalable data processing solutions on AWS.
- Modernize legacy ingestion frameworks using cloud-native services.
- Develop and optimize large-scale distributed data processing systems.
- Troubleshoot and support production data platforms and streaming applications.
- Collaborate with cross-functional teams on enterprise data integration initiatives.
Required Skills & Experience
- 10+ years of experience in Data Engineering, Software Engineering, or related fields.
- Strong expertise in AWS Cloud Services and cloud-native architectures.
- Hands-on experience with Apache Spark (Scala & PySpark).
- Strong knowledge of the Hadoop Ecosystem and distributed computing.
- Experience with Kafka, streaming technologies, and real-time data pipelines.
- Experience with AWS Kinesis, Kinesis Firehose, Flume, or similar ingestion platforms.
- Strong programming skills in Python, Scala, and Java.
- Experience with Big Data, Enterprise Data Warehousing, and Distributed Systems.
