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# AWS Data Engineer

- **Company:** Microgreen Technologies Llc
- **Location:** Plano, TX, United States
- **Contract:** Contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Apache HTTP Server, Microsoft Azure, Big Data, Computer Programming, Databases, Continuous Integration, Information Engineering, Data Integration, DevOps, Amazon DynamoDB, Python (Programming Language), PostgreSQL, Microsoft Copilot, Systems Integration, Data Processing, Scripting, Google Cloud, Data Ingestion, Snowflake, Apache Spark, Boto3, Agentic-AI, Git, Data Lakes, Pyspark, Deployment Automation, AWS Glue, AWS Data Analytics, Bitbucket, Claude, Api Design, Cloudwatch, Terraform, Splunk, Data Pipelines, Jenkins, Servicenow, Databricks, Control M
- **Published:** November 10, 2026
- **Apply:** https://www.dice.com/job-detail/d4645cf9-ee1c-4e4a-9eb1-7720d2b6374e

## About the Role

We are seeking a hands-on AWS Data Engineer with strong experience in AWS data services, Python development, and end-to-end data pipeline development. The ideal candidate should have experience building production-grade data pipelines from scratch, working with AWS data lakes, databases, and CI/CD deployments.

Must-Have Technical Skills

 * AWS Data Services: Strong hands-on experience with S3, Glue, Lambda, Step Functions, and Lake Formation.
 * Python: Strong Python programming, scripting, API development, and Boto3.
 * Data Engineering: Experience designing and developing end-to-end data pipelines, including data ingestion, transformation, and integration.
 * Databases: Strong knowledge of PostgreSQL and DynamoDB.
 * Big Data: Hands-on experience with Apache Spark and PySpark.
 * AWS Data Lake: Experience developing and managing AWS-based data lake solutions.
 * CI/CD & DevOps: Experience with Jenkins, Bitbucket/Git, Terraform, and automated deployments.
 * Monitoring: Experience with AWS CloudWatch and Splunk.
 * Additional Tools: Familiarity with ServiceNow and enterprise deployment processes.
 * AI Exposure: Basic understanding of Copilot, Claude, AI agents, and agentic workflows.

Good-to-Have Skills

 * Snowflake, including Horizon Catalog.
 * Databricks and Unity Catalog.
 * Apache Iceberg.
 * AWS Athena, Redshift, EMR, and S3 Select.
 * AWS EC2 and Control-M scheduling.
 * AWS Bedrock and AI application integrations.
 * Exposure to Google Cloud or Microsoft Azure.
 * Java/Scala programming knowledge., * Strong hands-on AWS Data Engineering and Python development experience.
 * Proven ability to build data pipelines from scratch.
 * Strong understanding of AWS data lake architecture and database technologies.
 * Developers preferred over candidates focused primarily on support, maintenance, or architecture.
 * Ability to work independently in a production environment.

## Description

* Design, develop, and maintain scalable AWS-based data pipelines.
 * Build data ingestion and transformation workflows using AWS Glue, Lambda, and Step Functions.
 * Develop Python scripts, APIs, and automation using Boto3.
 * Implement and manage AWS data lake solutions using S3 and Lake Formation.
 * Work with PostgreSQL, DynamoDB, Spark, and PySpark for data processing.
 * Implement CI/CD pipelines and automate deployments using Jenkins, Bitbucket, and Terraform.
 * Monitor data pipelines and troubleshoot issues using CloudWatch and Splunk.
 * Collaborate with cross-functional teams to deliver reliable data integration solutions.