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.)
* Ensure the best possible performance and quality of high scale data engineering project
* Participate in the architecture and system design discussions
* Independently perform hands on development and unit testing of the applications.
* Collaborate with the development team and build individual components into complex enterprise web systems.
* 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.
* Responsible to identify and resolve any performance issues
* Keep up to date with new technology development and implementation
* Participate in code review to make sure standards and best practices are met.
Job Requirements
Qualifications:
* Bachelor's degree in computer science, Software Engineering, MIS or equivalent combination of education and experience
* 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.
* Should have good experience with AWS Services - API Gateway, Lambda, Step Functions, SQS, DynamoDB, S3, Elasticsearch
* Serverless application development using AWS Lambda
* 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
* Good understanding of Lakehouse/data cloud architecture
