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# AWS Data Engineer

- **Company:** IT America
- **Location:** Richmond, VA, United States
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Amazon Web Services, Big Data, Cloud Computing, Information Engineering, Software Debugging, Distributed Computing Environment, Apache Hadoop, Python (Programming Language), SQL Databases, Data Logging, Data Processing, Data Ingestion, Apache Spark, Pyspark, Information Technology, AWS Glue, AWS Data Analytics, Data Pipelines, Serverless Computing
- **Published:** November 4, 2026
- **Apply:** https://www.thejobnetwork.com/job/744f2974-495e-4b6f-8247-5474b890b743/aws-data-engineer

## About the Role

* Bachelor's degree in Computer Science, Engineering, or related field.
 * Demonstrated expertise in developing data pipelines with Python and PySpark, with a strong emphasis on utilizing AWS Glue, EMR, and Step Functions.
 * Proficiency in SQL for data manipulation and querying.
 * Experience with distributed computing frameworks like Hadoop and Spark.
 * Strong understanding of cloud computing principles and experience with AWS services.
 * Excellent problem-solving and communication skills, with the ability to work collaboratively in a team environment.
 * Familiarity with Agile development methodologies is advantageous.

## Description

* Develop and optimize scalable data pipelines using Python and PySpark, with a primary focus on leveraging AWS services like Glue, EMR, and Step Functions.
 * Design, implement, and maintain data processing systems utilizing the capabilities of AWS Glue for data ingestion, transformation, and orchestration.
 * Utilize EMR clusters for distributed data processing and analytics, ensuring efficient resource utilization and performance.
 * Implement serverless workflows using AWS Step Functions to orchestrate complex data processing tasks and workflows.
 * Collaborate closely with cross-functional teams to understand data requirements and translate them into scalable and efficient solutions.
 * Ensure data quality, governance, and security standards are adhered to throughout the data pipeline.
 * Troubleshoot and debug data-related issues in production environments, leveraging AWS monitoring and logging tools.
 * Stay abreast of the latest advancements in big data technologies, AWS services, and best practices in data engineering.