AWS Data Engineer cum Data Scientist

Role Overview

We are looking for an Data Science AWS Engineer to join India Data Science team of DolFinTech, USA. The candidate must have at least 1 year of direct hands-on experience in developing, deploying, integrating, and monitoring Machine Learning models and processes on AWS. The candidate must have hands-on experience with Amazon SageMaker, AWS Lambda, API Gateway, S3, CloudWatch, and AWS-based ETL/data pipelines.

Key Responsibilities

• Develop, package, and deploy ML models using Amazon SageMaker .
• Build and manage real-time SageMaker inference endpoints .
• Develop AWS Lambda functions for model invocation and application integration.
• Create and maintain REST/HTTP APIs using Amazon API Gateway .
• Build and maintain ETL/data-processing pipelines on AWS using services such as S3, Glue, Lambda, Athena, and/or Step Functions.
• Implement end-to-end ML scoring workflows such as:
• Application/API → API Gateway → Lambda → SageMaker → Response
• Implement logging, monitoring, and alerting using Amazon CloudWatch.
• Monitor model/API performance, latency, failures, and production issues.
• Troubleshoot AWS deployment, integration, and IAM/permission issues .
• Support model and code versioning and deployment across Development, UAT/Staging, and Production environments.
• Work with Data Scientists to convert notebook/prototype models into reliable production solutions.

Mandatory Skills

• Minimum 1 year of hands-on AWS and Machine Learning experience
• Strong hands-on experience with Amazon SageMaker, AWS Lambda , Amazon API Gateway, Amazon S3, Amazon CloudWatch, AWS IAM, AWS ETL/data-processing pipelines, AWS Glue, Athena
• Strong Python and SQL skills.
• Experience deploying ML models into production environments .
• Experience creating and consuming REST APIs / JSON interfaces .
• Experience with Git/version control .
• Good understanding of ML models, feature engineering, model scoring, and model monitoring.

Preferred Skills

Experience with some of the following would be advantageous:

AWS Step Functions / Event Bridge

• SageMaker Pipelines / Model Registry / Model Monitor
• Docker / Amazon ECR
• CI/CD pipelines
• Terraform / CloudFormation / AWS CDK
• Fraud, credit risk, transaction risk, or financial-services models

Experience & Qualification

• 1+ years overall experience preferred
• Minimum 1 year of direct hands-on AWS experience
• Bachelor’s/Master’s degree in Computer Science, Engineering, Data Science, or a related discipline