AWS Data Engineer

Job Title - AWS Data Engineer

Relevant Years of Experience - 4+ Years

Location - Bangalore

Notice Period - Immediate to 30 Days

Roles&Responsibilities:

• Design, build, and maintain scalable data pipelines supporting batch, near-real-time, API, and streaming ingestion patterns from enterprise and external data sources
• Develop and optimize ETL/ELT workflows across raw, enriched, and curated data layers within a cloud-based lakehouse environment
• Implement and manage data storage solutions for structured, unstructured, and semi-structured data
• Collaborate with data architects to translate platform designs into reliable, production-grade implementations
• Apply and enforce data governance standards including data quality checks, lineage tracking, classification tagging, and access controls
• Build and maintain reusable data products that serve AI/ML and analytics consumers across multiple business domains
• Monitor pipeline health and implement observability, logging, and alerting practices to ensure data reliability
• Work with orchestration and scheduling tools to automate and manage complex data workflows
• Partner with security teams to ensure pipelines adhere to data classification and compliance requirements
• Contribute to platform documentation, code reviews, and engineering best practices

Job Requirements:

• 4+ years of experience in data engineering, ETL development, or a closely related role
• Strong hands-on experience building data pipelines on AWS cloud platforms
• Proficiency with ETL/ELT frameworks and workflow orchestration tools
• Experience working with lakehouse or data lake architectures and multi-zone storage patterns (landing, raw, enriched/curated)
• Solid programming skills in Python and/or SQL; familiarity with CLI and infrastructure-as-code tools is a plus
• Experience with structured, unstructured, and semi-structured data processing
• Familiarity with data governance, data quality, and metadata management concepts
• Understanding of streaming and real-time data processing patterns
• Ability to work effectively in a large, cross-functional, and matrixed enterprise environment
• Strong problem-solving skills and attention to detail.