Data Engineer

Title: Data Engineer **Location: Woodbury, MN (Primarily Onsite 5 days/week with Some Flexibility)

Duration: Initial 3-Month Contract with Potential Month-to-Month Extensions** Must have skills: DBT, Spark, Airflow, Python Overview Our client is seeking a Data Engineer to help accelerate a major analytics initiative with the goal of delivering a customer-facing analytics platform by year-end. These consultants will be responsible for building scalable data pipelines, transforming and modeling data, exposing data through APIs, and enabling rich analytics experiences for customers.

The team is focused on creating a seamless way for customers to access, analyze, and consume their data, whether through the company's portal or their own BI tools. These individuals will collaborate with a team of approximately five other professionals and play a key role in building the data foundation that powers the user experience.

Responsibilities

• Design, build, and maintain scalable data pipelines and integration processes.
• Develop and manage data transformation workflows using DBT.
• Build and optimize ETL/ELT processes utilizing PySpark, Airflow, and Python.
• Work within an on-premises environment to ingest, process, and deliver data efficiently.
• Expose customer data through APIs, enabling customers to consume data within their own BI and analytics platforms.
• Support the development of highly visual analytics experiences through semantic and visualization layers such as Cube.dev or similar technologies.
• Partner closely with developers responsible for building customer-facing applications and dashboards.
• Leverage AI tools, including Claude, to improve development efficiency and accelerate delivery.
• Collaborate with business and technical stakeholders to ensure solutions align with product objectives and customer needs.
• Contribute to the architecture and strategy of a modern analytics platform.

Required Qualifications

• 4+ years of Data Engineering experience.
• Strong experience with DBT, PySpark, and Apache Airflow.
• Experience building scalable data pipelines and transformation frameworks.
• Strong SQL and Python skills.
• Experience developing APIs or supporting API-driven data delivery.
• Experience working within on-premises data environments.
• Ability to work independently while collaborating effectively within a team environment.

Preferred Qualifications

• Experience with Cube.dev or similar semantic layer and analytics visualization technologies.
• Exposure to AI-assisted development tools, particularly Claude.
• Experience supporting customer-facing analytics, reporting, or data product initiatives.
• Familiarity with modern data architecture and best practices.

Ideal Candidate The ideal candidate is a hands-on Data Engineer who enjoys building modern data platforms, transforming complex data into meaningful insights, and enabling customers to access and visualize their data in intuitive ways. This person will be comfortable working across data engineering, API development, analytics enablement, and emerging AI technologies in a collaborative, fast-moving environment.