Desired Skills & Experience

• 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 Informatic).
• 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 the production environment.
• Participate in client design workshops and provide trade offs and recommendations towards building solutions.
• Mentor other engineers in coding best practices and problem solving
• Working experience in a cloud-native environment in one of the 3 major public clouds (GCP, AWS, Azure), at least 3 years of experience on AWS is preferred
• Experience and knowledge of Big Data Architecture, 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 delivering 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.
• Experience working with source code management tools such as AWS CodeCommit or GitHub.
• 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.