Senior Data & ML Engineer – AWS

About the role

This senior position sits at the intersection of data engineering and applied machine learning, focusing on building scalable, cloud‑native data platforms on AWS for a South‑African partner. You will design modern data lakes, streaming pipelines, and ML‑driven services that power analytics and intelligent automation across enterprise systems.

Key responsibilities

• Design and implement multi‑zone data lake architectures on Amazon S3, including raw, curated, and analytics‑ready layers.
• Build and maintain batch and real‑time pipelines using AWS Glue, Kinesis, Step Functions, and Lambda.
• Develop ETL workflows, data transformations, and metadata management with AWS Glue Data Catalog.
• Deploy, tune, and monitor machine‑learning models on Amazon SageMaker for prediction, scoring, and segmentation.
• Integrate generative AI capabilities via Amazon Bedrock to enable automation and personalization.
• Support data migration from Azure to AWS, handling schema mapping, validation, and performance optimization.
• Implement data governance, security, and access controls using AWS Lake Formation.
• Collaborate with cross‑functional teams to define architecture, maintain documentation, and ensure data quality.

Required profile

• 5+ years of experience in data engineering or ML engineering, with at least 2 years focused on AWS.
• Strong proficiency in Python and SQL.
• Hands‑on experience building scalable data pipelines and production‑grade ML services.
• Demonstrated ability to work in collaborative, multi‑disciplinary environments.

Required skills

• Python
• SQL
• AWS services: S3, Glue, Athena, Kinesis, Lambda, Step Functions, Lake Formation
• Amazon SageMaker
• Amazon Bedrock (or other generative AI frameworks)
• Data lake architecture and governance