
| Location: | not specified |
| Openings: | 1 |
| Salary Range: |
Description:
Requirement: AWS Data Engineer
Qualifications Required :
Bachelor’s Degree preferably in Computer Science, Engineering, Management Information Systems, or equivalent work experience.
6 to 10+ years of full stack software development with an emphasis on architecting, designing, implementing, testing and delivering highly scalable web and client/server solutions.
6-10+ years of experience in Data Engineering development
Strong experience with:
• AWS Glue - Python, Big Data – Pyspark, Control-M – ETL Batch job implementation stack
• Kinesis, Kafka, SNS – Real time message processing
• AWS Aurora, Dynamo, S3 – Data Storage
• AWS IAM, Cloud formation, Bamboo – Infra as code and CI/CD
• Lambda, Step function – Orchestration
• SQL
Secondary
Skills:
• CloudWatch, Event Bridge, Amazon EKS, Honeycomb, Redshift, AWS ALB
Good to have knowledge on:
• Design patterns/solid principles, Architectural patterns around microservices, Batch and Real time, Database decision , Memory management, Performance Tuning, Cost Optimization
• Prior experience with Database administration & migration & modernization in AWS Cloud
• Data Modelling and designing
• Experience writing SQL/Functions/Procedures in transactional database systems such as Oracle, SQL Server, DB2
• Extensive expertise in building CI/CD pipelines,containers, AWS and IaC
• Understanding of ALC, DB2 mainframe database
• Demonstrated project experience and skills in information requirements gathering, current state analysis, building data models, data architecture and data management process definition
• Experienced in creating polished high- and low-level design documentation, to facilitate the development cycle
• Extensive experience leading development teams to provide technical deliverables in accordance with SDLC methodologies such as SCRUM and Agile
• Great experience with performing code reviews and recommending automated review tools
• Experience with mentoring others in development technologies, processes, and tools