Data Engineer - Python & AWS Data Pipelines

Robotic Technologies Automation; Plano (TX); On-site; USD 110,000 - 150,000; Full time

Job summary

Robotic Technologies Automation is seeking a hands-on Data Engineer to build and maintain data pipelines using Python and AWS Glue Data Platforms. You will work with S3, Glue, Lake Formation, and CI/CD tools to ensure reliable data flows across enterprise platforms.

Ideal candidates have strong Python skills, practical AWS experience, and be comfortable implementing, testing, and maintaining production data pipelines in a fast-paced environment.

Qualifications

• Strong hands-on Python programming experience.
• Practical AWS experience with S3, AWS CLI, EC2, Glue, and Lake Formation.
• Understanding of data lakes and data pipeline development.
• Experience with CI/CD pipelines, Jenkins, and Bitbucket.
• Ability to build, test, troubleshoot, and maintain production data pipelines.

Responsibilities

• Build and maintain data pipelines using Python and AWS services.
• Develop data ingestion and connectivity solutions for enterprise data platforms.
• Work with AWS data lake services, including S3, Glue, and Lake Formation.
• Use AWS CLI and EC2 to support data engineering workloads.
• Implement and maintain CI/CD pipelines using Jenkins and Bitbucket.
• Troubleshoot data pipeline issues and improve data quality and reliability.
• Collaborate with platform and engineering teams to support shared data services.

Skills

Python programming

AWS data services

Data pipeline development

CI/CD pipelines

Tools

AWS S3

AWS CLI

EC2

Glue

Lake Formation

Jenkins

Bitbucket

Snowflake

Databricks

Apache Iceberg

Terraform

PySpark

Apache Spark

Job description

Robotic Technologies Automation is seeking a hands-on Data Engineer to build and maintain data pipelines using Python and AWS Glue Data Platforms. You will work with S3, Glue, Lake Formation, and CI/CD tools to ensure reliable data flows across enterprise platforms.

Ideal candidates have strong Python skills, practical AWS experience, and be comfortable implementing, testing, and maintaining production data pipelines in a fast-paced environment.