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Microgreen Technologies LLC

AWS Data Engineer

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Job Description

Please find the job description below. Need OR this is with
JPMC C2H
role The rate I can pay is $ 55-60 per hour need candidates with 8+ years of experience. Need Strong AWS experience. Must-Have Skills AWS (Strong Hands-On): Extensive experience with AWS data services, particularly S3, AWS Glue, Lake Formation, Lambda, Step Functions, and AWS CLI. Python (Strong): Hands-on Python development, scripting, APIs, and data pipeline development.
Data Pipeline Development:
Experience building production data pipelines from scratch, including ingestion, transformation, and cross-platform data connectivity.
Database Skills:
Strong database knowledge, particularly PostgreSQL and DynamoDB. Apache Spark /
PySpark:
Experience with distributed data processing and data engineering workloads.
AWS Data Lake:
Hands-on experience working with AWS-based data lake environments and data integration.
CI/CD Pipelines:
Experience with Jenkins, Bitbucket, and automated code deployment across environments.
DevOps Tools:
Familiarity with ServiceNow and enterprise code promotion, governance, and deployment processes.
Hands-On Development:
Must be a strong developer capable of independently building AWS Lambda functions and end-to-end data pipelines, not an architecture-only candidate.
Good-to-Have Skills Snowflake:
Experience working with Snowflake data platforms and integrations.
Databricks:
Exposure to Databricks and interoperability between data platforms.
Apache Iceberg:
Understanding of Iceberg tables, data lake interoperability, and cross-platform data sharing.
Agentic AI:
Basic understanding of AI agents, agent creation, and agentic workflows.
AWS Bedrock:
Basic knowledge of Amazon Bedrock and its integration with AI applications.
AI Tools:
Familiarity with AI tools and their integration into development workflows. Google Cloud /
Azure:
Exposure to additional cloud platforms is beneficial but not required.