Job Description :

Location : Bangalore

Job Mode : Hybrid

Must Have :

- 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.

- Good analytical & problem-solving skills.

- Good communication and presentation skills.