Role: Data Engineering /n Notice Period: Immediately to 15 days /n Experience: 5–10 Years /n Location: Bangalore /n Must Have /n /n
Experience in architecting and delivering highly scalable, distributed, cloud-based enterprise data solutions.
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Strong expertise in the end-to-end implementation of Cloud data engineering solutions like Enterprise Data Lake, Data hub in AWS.
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Hands-on experience with Snowflake utilities, SnowSQL, SnowPipe, ETL data Pipelines, Big Data model techniques using Python / Java.
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Experience in loading disparate data sets and translating complex functional and technical requirements into detailed design.
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Should be aware of deploying Snowflake features such as data sharing, events and lake-house patterns.
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Should have experience with data security and data access controls and design.
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Deep understanding of relational as well as NoSQL data stores, methods and approaches (star and snowflake, dimensional modeling).
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Proficient in Lambda and Kappa Architectures.
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Robust AWS hands-on expertise with a programming background preferably Python/Scala.
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Good knowledge of Big Data frameworks and related technologies - Experience in Hadoop and Spark is mandatory.
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Solid experience in AWS compute services like AWS EMR, Glue and Sagemaker and storage services like S3, Redshift & Dynamodb.
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Good experience with any one of the AWS Streaming Services like AWS Kinesis, AWS SQS and AWS MSK.
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Troubleshooting and Performance tuning experience in Spark framework - Spark core, Sql and Spark Streaming.
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Experience in one of the flow tools like Airflow, Nifi or Luigi.
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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.