Posted:1 day ago|
Platform:
On-site
Full Time
• Design, develop, and optimize Big Data architectures leveraging AWS services for large-scale, complex data processing.
• Build and maintain data pipelines using Spark (Scala) for both structured and unstructured datasets.
• Architect and operationalize data engineering and analytics platforms (AWS preferred; Hortonworks, Cloudera, or MapR experience a plus).
• Implement and manage AWS services including EMR, Glue, Kinesis, DynamoDB, Athena, CloudFormation, API Gateway, and S3.
• Work on real-time streaming solutions using Kafka and AWS Kinesis.
• Support ML model operationalization on AWS (deployment, scheduling, and monitoring).
• Analyze source system data and data flows to ensure high-quality, reliable data delivery for business needs.
• Write highly efficient SQL queries and support data warehouse initiatives using Apache NiFi, Airflow, and Kylo.
• Collaborate with cross-functional teams to provide technical leadership, mentor team members, and strengthen the data engineering capability.
• Troubleshoot and resolve complex technical issues, ensuring scalability, performance, and security of data solutions.
• Solid hands-on experience in Big Data Technologies (AWS, Scala, Hadoop, and Spark Mandatory)
• Proven expertise in Spark with Scala
• Hands-on experience with: AWS services (EMR, Glue, Lambda, S3, CloudFormation, API Gateway, Athena, Lake Formation)
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