Responsibilities:
1) Possesses 4-6 years of experience in developing and architecting with AWS data engineering solutions.
2) Design, build and operationalize large scale enterprise data solutions and applications using one or more of AWS data and analytics services S3, Glue, Lambda, SNS, EC2, RedShift, IAM and KMS 3) Should be able gather requirement from the analytics partners, propose the best cloud solution and implement it.
4) Follow established project execution processes, coding standard and industry best practices.
5) Should be aware about AWS and Data security principles.
6) Get actively involved in Training, self-development & knowledge sharing
7) Actively contribute to the organization level cloud initiatives.
8) Problem solver with analytical thinking and ability to apply root cause analysis.
9) Should have good learning attitude to quickly learn and implement any new Service/technology or enterprise guided initiatives.
10) Focus on continuous improvement in solutions and as individuals
11) Can easily adapt between working independently or collaboratively on a team
12) Experience in BI , Python , AWS services S3, Glue, Lambda, SNS, EC2, RedShift, IAM and KMS, CI/CD Pipelines in GitHub Qualifications:
Skills set:

• 3-6 years of experience in being a data engineer
• Experience with Python language, SQL and working with relational databases
• Experience building and optimizing data pipelines, architectures, and data sets.
• Experience with CI/CD Pipelines in GitHub and Jenkins
• Excellent communication and collaboration skills, Ability to communicate what is relevant and important in a clear and concise manner.

Must have Skills: Experience with AWS services S3, Glue, Lambda, SNS, EC2, RedShift, IAM and KMS, CI/CD Pipelines in GitHub


Good to have Skills: Hands on experience/Familiarity with one/more of the following technologies: Database, Data Visualization (Power BI), Scripting, ETL (Informatica PowerCenter)