● Experience in architecting and delivering highly scalable, distributed, cloud-based enterprise data solutions
● Strong expertise in the end-to-end implementation of Cloud data engineering solutions like
Enterprise Data Lake, Data hub in AWS
● Hands-on experience with Snowflake utilities, SnowSQL, SnowPipe, ETL data Pipelines, Big Datamodel techniques using Python / Java
● Experience in loading disparate data sets and translating complex functional and technical
requirements into detailed design
● Should be aware of deploying Snowflake features such as data sharing, events and lake-house patterns
● Should have experience with data security and data access controls and design
● Deep understanding of relational as well as NoSQL data stores, methods and approaches (star and snowflake, dimensional modeling)
● Proficient in Lambda and Kappa Architectures
● Strong AWS hands-on expertise with a programming background preferably Python/Scala
● Good knowledge of Big Data frameworks and related technologies - Experience in Hadoop and Spark is mandatory
● Strong experience in AWS compute services like AWS EMR, Glue and Sagemaker and storage services like S3, Redshift & Dynamodb
● Good experience with any one of the AWS Streaming Services like AWS Kinesis, AWS SQS and AWS MSK
● Troubleshooting and Performance tuning experience in Spark framework - Spark core, Sql and Spark Streaming
● Experience in one of the flow tools like Airflow, Nifi or Luigi
● Good knowledge of Application DevOps tools (Git, CI/CD Frameworks) - Experience in Jenkins or Gitlab with rich experience in source code management like Code Pipeline, Code Build and Code Commit