Data Engineer

Hollstadt Consulting is a management and technology consulting firm dedicated to placing professionals at engagements where they will excel. When you work with us, you'll work with a refreshingly real company led and staffed by seasoned experts who are also down-to-earth, good people. We're committed to treating you with respect and helping you achieve your career aspirations.

Since 1990, Hollstadt has been a trusted partner to more than 150 domestic and global companies and has successfully completed over 3,000 projects. Our continued growth has created challenging and rewarding opportunities for accomplished IT and Business Consultants. Hollstadt Consulting is an equal opportunity employer including disability/veteran.

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Role: Data Engineer

Location: Hybrid in Bloomington, MN preferred; approximately 1–2 days onsite per week

Employment Type: Six-month contract-to-hire

Citizenship Requirement: Must be a U.S. citizen

Target Start: Around 9/7/2026

Rate: $70-$80/hour W2

The Data Engineer will help build the foundational data capabilities needed to support business intelligence, manufacturing analytics, AI, security, and enterprise reporting across a complex semiconductor manufacturing environment.

The company currently has a dedicated AI team but is building out its broader data and BI capabilities. The Data Engineer will work with a newly forming data organization, technical leadership, AI engineers, business analysts, manufacturing teams, and enterprise IT to ingest, transform, organize, classify, and make data usable across the company.

A major initial focus will be reverse engineering and modernizing a legacy data environment that includes manufacturing systems, older databases, disconnected applications, data warehouses, data marts, and systems that currently lack sufficient metadata, ownership attribution, and security classifications.

• Design, develop, and maintain pipelines that ingest data from enterprise, manufacturing, customer-facing, and legacy systems.
• Bring data that is currently disconnected or inaccessible into the company’s data lake, warehouse, analytics, and AI environments.
• Profile legacy data to understand its structure, quality, business meaning, sensitivity, ownership, and downstream use.
• Develop transformation and enrichment processes that add necessary classifications, metadata, ownership, and security attributes.
• Support rule-based and AI-assisted approaches for identifying sensitive, customer-owned, regulated, or restricted data.
• Partner with business analysts and stakeholders to translate data requirements into scalable technical solutions.
• Help design and improve data lakes, data warehouses, data marts, and related data architecture.
• Support modernization initiatives involving legacy manufacturing systems and databases, including movement from older platforms into SQL-based environments.
• Prepare data structures that allow infrastructure and security teams to implement row-level security and role-based access.
• Build and maintain reliable data flows supporting business intelligence, reporting, advanced analytics, and AI use cases.
• Monitor data quality, pipeline reliability, job performance, exceptions, and processing failures.
• Identify systems or datasets that cannot be effectively remediated and provide technical input into migration or replacement decisions.
• Document source-to-target…