Position Details
About this role
This role involves developing and operating scalable data ingestion and transformation pipelines to support AI and analytics platforms within AWS, focusing on petabyte-scale data processing and ML deployment.
Key Responsibilities
- Design and operate data pipelines
- Deploy ML models
- Transform raw data into structured datasets
- Ensure platform resilience
- Automate data workflows
Technical Overview
Involves building data pipelines using AWS services like Glue, EMR, Spark, and deploying ML models with SageMaker, ECS, and EKS, supporting large-scale data analytics and AI initiatives.
Ideal Candidate
The ideal candidate is a mid-level data engineer with experience in building scalable data pipelines, deploying ML models on AWS, and working with big data tools like Spark, Athena, and Redshift, capable of supporting AI-driven analytics platforms.
Must-Have Skills
Nice-to-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
Lack of experience with AWS data tools, No background in data pipelines or ML deployment, Inability to work in a fast-paced environment, Lack of collaboration skills
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