Data Engineer: Python & AWS Data Pipelines

MACHINE LEARNING TECHNOLOGIES LLC; Plano (TX); On-site; USD 120,000 - 150,000; Full time

Job summary

Machine Learning Technologies LLC in Plano, TX seeks a hands-on Data Engineer with strong Python and AWS experience to build and maintain data pipelines across enterprise platforms. The role emphasizes reliable data integrations, data lake/lakehouse support, and connectivity rather than broad enterprise architecture.

You will develop ingestion solutions, leverage S3/Glue/Lake Formation, and implement CI/CD pipelines with Jenkins and Bitbucket, collaborating with platform teams to ensure data

Qualifications

• Hands-on Python programming experience.
• Experience with AWS data services (S3, Glue, Lake Formation) and data lake concepts.
• Experience building and maintaining production-grade data pipelines with CI/CD tooling (Jenkins/Bitbucket).

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

AWS

Data pipelines

Jenkins

Bitbucket

S3

Glue

Tools

Snowflake

Databricks

Apache Iceberg

Terraform

PySpark

Apache Spark

Job description

Machine Learning Technologies LLC in Plano, TX seeks a hands-on Data Engineer with strong Python and AWS experience to build and maintain data pipelines across enterprise platforms. The role emphasizes reliable data integrations, data lake/lakehouse support, and connectivity rather than broad enterprise architecture.

You will develop ingestion solutions, leverage S3/Glue/Lake Formation, and implement CI/CD pipelines with Jenkins and Bitbucket, collaborating with platform teams to ensure data