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;