Data Engineer - Flexible, Cloud-Driven Pipelines

Linden Summit Corp.; Saint Paul (MN); On-site; USD 90,000 - 140,000; Full time

Benefits offered by this job

Health insurance

Employer 401(k) matching

Professional development

Flexible work environment

Wellness programs

Employee discounts

Job summary

Linden Summit Corp. in Saint Paul, MN is seeking a Data Engineer to design, build, and maintain data infrastructure that supports business operations.

This full-time role offers a negotiable salary and a path to growth within a manufacturing environment. You will design data pipelines, ensure data quality, and optimize storage and performance while collaborating with cross-functional teams to translate data requirements into scalable solutions.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience as a Data Engineer or similar role.
• Proficiency in SQL, Python, and data modeling techniques.
• Experience with cloud platforms such as AWS or Azure.

Responsibilities

• Design and implement data pipelines to collect, process, and store data from various sources.
• Ensure data quality and integrity by implementing data validation and cleansing processes.
• Optimize data storage and retrieval systems for performance and scalability.
• Collaborate with cross-functional teams to identify data requirements and deliver data-driven insights.
• Monitor and troubleshoot data infrastructure to ensure high availability and reliability.
• Maintain and document data engineering processes and procedures.

Skills

SQL

Python

Data modeling

ETL processes

Data pipelines

AWS

Azure

Hadoop

Spark

Hive

Education

Bachelor's degree in Computer Science or Engineering

Tools

Airflow

dbt

Job description

Linden Summit Corp. in Saint Paul, MN is seeking a Data Engineer to design, build, and maintain data infrastructure that supports business operations.

This full-time role offers a negotiable salary and a path to growth within a manufacturing environment. You will design data pipelines, ensure data quality, and optimize storage and performance while collaborating with cross-functional teams to translate data requirements into scalable solutions.