Data Engineer

Company: US Main
Location: Minneapolis
Posted on: April 17, 2025

Job Description:

Design, develop, and maintain scalable, efficient, and reliable data pipelines for collecting, processing, integrating, and storing data from diverse sources including databases, APIs, data warehouses, and external systems. Ensure near real-time data pipeline performance and scalability through continuous optimization and monitoring.

Making sure you fit the guidelines as an applicant for this role is essential, please read the below carefully.

Implement best practices in data management to ensure high data quality through cleansing, normalization, enrichment, and validation techniques. Apply rigorous data governance strategies to maintain consistency, accuracy, and completeness across datasets.

Develop and manage modern data storage solutions such as data lakes and data warehouses, ensuring efficient data organization, retrieval, and usability. Optimize data processing workflows using tools like Airflow, Spark, Kafka, and Fivetran, and enhance query performance through caching, indexing, and system tuning.

Ensure the security and compliance of all data assets by implementing robust access controls, auditing mechanisms, and adherence to industry regulations. Monitor and audit data usage to detect and prevent unauthorized access, while safeguarding sensitive information.

Collaborate cross-functionally with business analysts, software engineers, and data scientists to understand data needs and translate them into actionable data solutions. Support the organization's data strategy by aligning engineering efforts with business goals and analytics initiatives.

Play a critical role in transforming raw data into valuable insights through advanced analytics, partnering with analysts to design models and visualizations that drive decision-making. Ensure that data used for business intelligence, AI, and ML is trustworthy, well-documented, and easily accessible.

Champion the governance of data and analytical models to mitigate risks and ensure accountability in automated decision-making systems. Implement quality checks directly within data pipelines to support compliance and risk management frameworks.

Work in close partnership with the Director of Data & Analytics and Data Platform Manager to shape the vision for treating data as a strategic business asset. Take ownership of enterprise data assets and analytics platforms to augment human performance and enable data-driven decision-making across the organization.

Qualifications

Bachelor's degree in Computer Science, Data Science, Software Engineering, Information Systems, or a related quantitative field.


5+ years of experience in data engineering or related fields, with strong capabilities in data integration, modeling, governance, quality, security, and performance optimization.


Deep expertise with modern data pipeline technologies such as Fivetran, Kafka, Apache Airflow, and Apache Spark.


Advanced proficiency in Python, Java, SQL, and data science tools such as R and SAS.


Strong command of cloud services (AWS, Azure) and modern data platforms (e.g., Snowflake).


Proven experience in data modeling, ETL/ELT development, and data warehousing best practices.


Hands-on experience with dbt for analytics engineering, including design and implementation of analytics code.


Deep understanding of data governance, security protocols, and compliance frameworks.


Excellent collaboration and communication skills, with the ability to work across teams with varying technical knowledge and to engage stakeholders from technical leads to executives.

Keywords: US Main, Eau Claire , Data Engineer, Engineering , Minneapolis, Wisconsin