Senior Data & ML Engineer (AWS)

About the role

This senior position sits at the intersection of data engineering and machine learning, focusing on building scalable, cloud‑native data platforms on AWS for a Saudi‑based 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 AWS S3 with 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 ML models in production using Amazon SageMaker.
• Integrate generative AI capabilities via Amazon Bedrock for automation and personalization.
• Support data migration from Azure to AWS, handling schema mapping, validation, and performance optimization.
• Implement data governance, security, and access controls with 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 data lake solutions.
• Proven track record deploying ML models in production on AWS.

Required skills

• Python
• SQL
• AWS S3
• AWS Glue
• AWS Athena
• AWS Kinesis
• AWS Lambda
• AWS Step Functions
• AWS Lake Formation
• Amazon SageMaker
• Amazon Bedrock