Data Engineer: Build Scalable Data Pipelines & Lakes

MACHINE LEARNING TECHNOLOGIES LLC; Alpharetta (GA); On-site; USD 94,000 - 127,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC is seeking an experienced Data Engineer in Georgia to design, develop, and maintain scalable data pipelines and processing solutions. You will work with Python, SQL, ETL/ELT, cloud platforms, data warehousing, and Big Data technologies to support analytics and data-driven decisions.

The role involves building ETL/ELT workflows, developing data processing solutions, and collaborating with Data Scientists, Analysts, and Business Teams in an Agile environment.

Qualifications

• Experience designing, developing, and maintaining scalable data pipelines.
• Expertise in Python, SQL, ETL/ELT, cloud platforms, data warehousing and Big Data tech.

Responsibilities

• Design, develop, and maintain scalable data pipelines.
• Build and optimize ETL/ELT workflows.
• Extract, transform, and load data from multiple sources.
• Develop data processing solutions using Python, SQL, and Spark.
• Implement data integration and data transformation processes.
• Design and maintain data warehouses and data lakes.
• Work with cloud-based data engineering platforms.
• Monitor and troubleshoot data pipeline performance.
• Ensure data accuracy, quality, security, and reliability.
• Collaborate with Data Scientists, Analysts, and Business Teams.
• Optimize SQL queries and improve data processing performance.
• Follow Agile methodologies and participate in technical discussions.

Skills

Python

SQL

ETL/ELT

Spark

Cloud platforms

Data warehousing

Big Data

Tools

AWS

GCP

Azure

Apache Airflow

Snowflake

Job description

MACHINE LEARNING TECHNOLOGIES LLC is seeking an experienced Data Engineer in Georgia to design, develop, and maintain scalable data pipelines and processing solutions. You will work with Python, SQL, ETL/ELT, cloud platforms, data warehousing, and Big Data technologies to support analytics and data-driven decisions.

The role involves building ETL/ELT workflows, developing data processing solutions, and collaborating with Data Scientists, Analysts, and Business Teams in an Agile environment.