Data Engineer

Design, develop, and maintain scalable data platform solutions across AWS and hybrid/on-premises environments. Build, optimize, and support production-grade data pipelines using Python, PySpark, SQL, and cloud-native technologies. Implement and maintain ETL/ELT workflows, Data Lake/Lakehouse architectures, metadata management, search platforms, and AI services.

Develop and maintain CI/CD pipelines, automated testing frameworks, deployment workflows, and infrastructure automation. Implement, integrate, and support AWS services and technologies such as OpenSearch, Amazon Bedrock, Agent

Core, MCP, and related platform components. Monitor and optimize platform performance, reliability, security, observability, and cost efficiency. Troubleshoot production incidents, perform root-cause analysis, and ensure platform stability and operational excellence.

Collaborate with data engineering, infrastructure, security, and application teams to drive platform modernization and continuous improvement. Mandatory

3–5+ years of hands-on experience building and supporting production-grade data pipelines using SQL, Python, and cloud technologies. Practical experience with AWS and/or hybrid cloud environments. Strong Linux/Unix administration, shell scripting, troubleshooting, and production support capabilities.

Solid understanding of data engineering principles, ETL/ELT processes, and distributed data processing. Technical Skills Programming & Data Processing: P