Description

Requirements:

  • Experience implementing, supporting data lakes, data warehouses and data applications on AWS for large enterprises
  • Programming experience with Python, Shell scripting and SQL
  • Solid experience of AWS services such as CloudFormation, S3, Athena , Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, SM etc.
  • Solid experience implementing solutions on AWS based data lakes.
  • Experience in AWS data lake/data warehouse/business analytics
  • Experience in system analysis, design, development, and implementation of data ingestion pipeline in AWS
  • Knowledge of ETL/ELT
  • End-to-end data solutions (ingest, storage, integration, processing, access) on AWS
  • Architect and implement CI/CD strategy for EDP
  • Implement high velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred)
  • Migrate data from traditional relational database systems, file systems, NAS shares to AWS relational databases such as Amazon RDS, Aurora, and Redshift
  • Migrate data from APIs to AWS data lake (S3) and relational databases such as Amazon RDS, Aurora, and Redshift
  • Implement POCs on any new technology or tools to be implemented on EDP and onboard for real use-case
  • AWS Solutions Architect or AWS Developer Certification preferred
  • Experience developing business applications using SQL databases.
  • Should have good experience with AWS Services – S3, Athena, Glue, Lambda, Step Functions, SQS, Redshift.
  • Knowledge of Snowflake is advantage

Responsibilities:

  • Designing, building, and maintaining efficient, reusable, and reliable architecture and code.
  • Build reliable and robust Data ingestion pipelines (within AWS, onprem to AWS, etc)
  • Independently perform hands on development and unit testing of the applications.
  • Work in a team environment with product, production operation, QE/QA and cross functional teams to deliver a project throughout the whole software development cycle;

Education

Any Graduate