Senior Data/ML Engineer (AWS)

About the role

We are seeking a Senior Data/ML Engineer with deep expertise in AWS to design and build scalable, cloud‑native data platforms. The role focuses on creating modern data lakes, streaming pipelines, and machine‑learning services that power analytics and intelligent automation across the enterprise.

Key responsibilities

• Design and implement multi‑zone data lake architectures on AWS S3, including raw, curated, and analytics‑ready layers.
• Build and maintain batch and real‑time data 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 ability to operationalize ML models in production environments.

Required skills

• Python
• SQL
• AWS S3
• AWS Glue
• AWS Athena
• AWS Kinesis
• AWS Lambda
• AWS Step Functions
• AWS Lake Formation
• Amazon SageMaker
• Amazon Bedrock
• Data lake architecture
• ETL workflow development
• Streaming and batch data pipelines
• Data governance and security