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AWS Software Engineer with AWS EMR, Glue, CloudWatch, Python, SQL

  • Source: Naukri
  • PwC
  • Hybrid
  • Bengaluru
  • Full-Time
  • Mid level

Job Description

Role & responsibilities:

  • 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 Data model 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
  • Experience with AWS CloudWatch, AWS Cloud Trail, AWS Account Config, AWS Config Rules
  • Strong understanding of Cloud data migration processes, methods and project lifecycle

Preferred candidate profile

  • Experience in building stream-processing systems, using solutions such as Storm or Spark-Streaming
  • Experience in Big Data ML toolkits, such as Mahout, SparkML, or H2O
  • Knowledge in Python
  • Worked in Offshore / Onsite Engagements
  • Experience in one of the flow tools like Airflow, Nifi or Luigi
  • Experience in AWS services like STEP & Lambda

Skills

  • amazon-web-services
  • amazon-emr
  • aws-glue
  • amazon-cloudwatch
  • Python
  • Snowflake
  • Java
  • Scala
  • Hadoop
  • apache-hadoop
  • Spark
  • amazon-s3
  • amazon-redshift
  • amazon-kinesis
  • amazon-sqs
  • spark-framework
  • apache-spark-streaming
  • Airflow
  • apache-airflow
  • luigi
  • Jenkins
  • gitlab
  • aws-config
  • aws-cloud-data-migration
  • apache-mahout
  • h2o
  • aws-lambda

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