Data Engineer - Build Scalable Data Pipelines (Louisville)

Sterling North LLC; Louisville (KY); On-site; USD 95,000 - 140,000; Full time

Benefits offered by this job

Health insurance

Retirement plan (401k)

Tuition reimbursement

Online courses and workshops

Job summary

Sterling North LLC in Louisville, KY is seeking a Data Engineer to design, develop, and maintain data pipelines that transform raw data into actionable insights for our logistics and supply chain operations.

You will collaborate with data scientists and analysts to translate business requirements into scalable technical solutions, optimize storage, and ensure pipeline reliability. A strong background in SQL, Python, and cloud data warehousing is essential.

Qualifications

• Bachelor's degree in Computer Science, Data Engineering, or a related field.
• 3-5 years of experience in data engineering, with a strong background in SQL and Python.
• Proficiency in data warehousing tools (Snowflake, BigQuery, Redshift).
• Experience with cloud platforms such as AWS or GCP.

Responsibilities

• Design, develop, and maintain data pipelines to support logistics and supply chain operations.
• Collaborate with data scientists and analysts to translate business requirements into technical solutions.
• Optimize data storage and retrieval processes to enhance performance and reduce costs.
• Monitor and troubleshoot data pipeline issues to ensure reliability and availability.
• Stay up-to-date with emerging technologies and best practices in data engineering.
• Mentor and guide junior team members to foster continuous learning.

Skills

SQL

Python

Problem-solving

Communication

Teamwork

Education

Bachelor's degree in Computer Science or related field

Tools

Snowflake

BigQuery

Redshift

AWS

GCP

Job description

Sterling North LLC in Louisville, KY is seeking a Data Engineer to design, develop, and maintain data pipelines that transform raw data into actionable insights for our logistics and supply chain operations.

You will collaborate with data scientists and analysts to translate business requirements into scalable technical solutions, optimize storage, and ensure pipeline reliability. A strong background in SQL, Python, and cloud data warehousing is essential.