Sr. Data Engineer

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

.

• 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