Data Engineer: Scalable Pipelines & AI Analytics

Hollstadt & Associates; Minnesota; On-site; USD 140,000 - 150,000; Full time

Benefits offered by this job

401k + Matching

Medical, dental, vision

Job summary

Hollstadt Consulting is seeking a Data Engineer in Minnesota to join a team building scalable data pipelines, modeling data across multiple datasets, and enabling analytics for data scientists and analysts. The role emphasizes cloud-first design, governance, and cross-functional collaboration.

The candidate will work with stakeholders, ensure data quality, and contribute to a culture of learning while supporting enterprise-wide data initiatives.

Qualifications

• Healthcare Administration and Operations Data Domain background required.
• Bachelor’s degree in CS/Data or related quantitative field and 4+ years in analytics, data science, or engineering.
• 5+ years programming in at least two languages: SQL, Python, Java, R or Spark.
• Expert SQL and experience with Oracle, PostgreSQL, MySQL, or SQL Server.
• 4+ years in BI/Analytics tools such as Azure Data Factory, Synapse, Power BI, Databricks.

Responsibilities

• Frame problems with stakeholders and frame data requirements.
• Design scalable data pipelines for ingestion, cleansing, transformation, and validation.
• Collaborate with developers to design scalable data solutions.
• Adhere to data governance and compliance standards across pipelines.
• Perform root cause analysis and implement preventative fixes.
• Model data flows and storage across multiple pipelines.

Skills

SQL

Python

Java

R

Spark

Education

Bachelor’s degree in CS/Data or related quantitative field

Master’s degree in CS/Math/Software acceptable

Tools

Oracle

PostgreSQL

MySQL

SQL Server

Git

Job description

Hollstadt Consulting is seeking a Data Engineer in Minnesota to join a team building scalable data pipelines, modeling data across multiple datasets, and enabling analytics for data scientists and analysts. The role emphasizes cloud-first design, governance, and cross-functional collaboration.

The candidate will work with stakeholders, ensure data quality, and contribute to a culture of learning while supporting enterprise-wide data initiatives.