Base: 83,000 to 112,000; bonus/equity: not specifi...
On-site
Aws glue
Aws sagemaker
Apache airflow
This role will focus on designing and building robust data and ML feature inference pipelines with a strong emphasis on automation scalability and production grade solutions
Job Summary
This role will focus on designing and building robust data and ML feature inference pipelines with a strong emphasis on automation scalability and production grade solutions.
The engagement leverages an existing AWS production environment including data pipelines and ML workflows and involves migrating and integrating models from other teams into a centralized AWS based system.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees.
Matching Summary
This role will focus on designing and building robust data and ML feature inference pipelines with a strong emphasis on automation scalability and production grade solutions.
Salary
Base: 83,000 to 112,000; Bonus/Equity: Not specified; Benefits: Comprehensive package
Skills & Requirements
Must-have
AWS Glue
AWS SageMaker
Apache Airflow
Python, Java, SQL
Big data processing (Spark, Hadoop)
Data warehousing platforms
Data quality engineering
CI/CD
Nice-to-have
AI Agents and/or GenAI
AWS certifications
Financial services industry experience
Key Requirements
3 years of experience in programming using Python, Java or equivalent including proficiency with a SQL like language
3 years of experience delivering production software in Big data processing, Data warehousing platforms, Data quality engineering, CI/CD
1-3 years of experience building and/or maintaining machine learning models
Hands on experience with Apache Airflow
1-3 years of experience with AWS cloud services (AWS Glue, SageMaker, Athena)