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Virtusa
Responsibilities:
Create and maintain optimal data pipeline architecture by designing and implementing data ingestion solutions on AWS using AWS native services (such as GLUE, Lambda) or using data management technologies (such as Talend or Informatica)
Design and optimize data models on AWS Cloud using AWS data stores such as Redshift, DynamoDB, RDS, S3
Design operations architecture and conduct performance engineering for large scale data lakes in production environment
Participate in client design workshops and provide tradeoffs and recommendations towards building solutions.
Mentor other engineers in coding best practices and problem solving
Required Skills
Working experience in a cloud native environment in one of the 3 major public clouds (GCP, AWS, Azure), at least 5 year experience on AWS is preferred
Experience and knowledge of Big Data Architectures, cloud and on premise
AWS infrastructure and networking working experience
AWS Collection Services: Kinesis, Kafka, Database Migration Service
AWS main Storage Service: S3, RDS, Redshift, DynamoDB
AWS main Compute Service: EC2, Lambda, ECS, EKS
Experience in building and deliver proofs-of-concept, in order to address specific business needs, using the most appropriate techniques, data sources and technologies
Working experience in migrating workloads from on premise to cloud environment
Experience in monitoring distributed infrastructure, using AWS tools or open source ones Experience in monitoring distributed infrastructure, using AWS tools or open source ones such as CloudWatch, Prometheus, and the ELK stack
Proven experience in: Java, Scala, Python, and shell scripting
Working experience with: Apache Spark, Databricks, Azure Data Factory, Azure Synapse, and other Azure related ETL/ELT tools
AWS Certification: AWS Certified Solutions Architect and/or AWS Certified Data Analytics
Working experience with Agile Methodology and Kanban
SQL language knowledge
Experience working with source code management tools such as AWS CodeCommit or GitHub
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