Job Description:

AWS Cloud Software/Data Engineer for helping with AWS SageMaker Infra setup, Build ML/Data Pipeline & Prod ready code for Deploying ML Models

(Received from Data Scientists) in AWS SageMaker & Finally loading data into Strategic data sources like Snowflake for Analytics consumption. Experience in building reusable & structured Python code, Model/Data Pipeline & handling of large volume of data.

Building Data pipeline, Develops secure and high-quality production code in Python.
Deploying ML Models from Data Scientists in AWS Sage maker.
Strong working knowledge of Python programming language.
Experience in using AWS Sage maker for ML in cloud.
Knowledge of S3, Graph DB like AWS Neptune.
Experience with AWS services like Lambda, EC2, EMR, Redshift, Glue, S3, IAM, RDS, Aurora, DynamoDB etc.
Develops secure and high-quality production code, and reviews and debugs ML code written by Data Scientists.
Certified AWS Solutions Architect (Professional) or AWS DevOps Engineer or AWS Machine Learning/Database Specialty (Anyone of mentioned Certification is must).

Strong data engineer with DW Exp, Preferred DB Snowflake or Oracle.
Proficiency in automation and continuous delivery methods, Gitlab CI.
Proficient in all aspects of the Software Development Life Cycle.
Knowledge of API & Event interface for analytics.
Understanding of Information Governance.
Experience/Knowledge of Model Ops.