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Mid-level data engineer title, metro Bangalore location, broad AWS skills and known employer increase applicant competition.
Skills are transferable across industries but strong AWS lakehouse and platform engineering experience demands domain-specific background.
Explicit 6+ years, mandatory AWS/data platform, IaC and SageMaker experience create high filtering strictness.
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Design, develop, and maintain scalable ETL/ELT data pipelines and reusable platform capabilities using AWS data services, ensuring high performance, cost efficiency, and automation.
Lead automation and AI-augmented development initiatives to improve data engineering lifecycle productivity and accelerate delivery within an Agile team setting.
Manage CI/CD pipelines, Infrastructure as Code, observability, security, and documentation to ensure robust, compliant, and resilient data platform operations.
6+ years of experience in Data Engineering with strong skills in architecting scalable cloud-native data solutions on AWS.
Proficient in Python programming and AWS data technologies (e.g., Redshift, S3, Glue, Lambda); exposure to Terraform or CloudFormation for IaC.
Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.
Must reside within commutable distance to Bengaluru, India, with availability for onsite work at least 3 days per week.
Experienced in implementing modern data platform architectures such as medallion architecture, lakehouse, and data mesh in an enterprise environment.
Demonstrated ability to lead technical mentorship, enforce data governance standards, and deliver end-to-end data solutions collaboratively with cross-functional Agile teams.
Familiar with AI-enabled engineering tools (e.g., Claude Code), MLOps infrastructure (AWS SageMaker, Bedrock), and modern CI/CD and observability practices for operational excellence.