Data Engineer

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 Position Overview 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. Key Responsibilities • 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 mappings, transformations, technical dependencies, data models, and operational support procedures. • Collaborate with the AI team on manufacturing use cases such as pattern recognition, defect identification, yield improvement, and earlier detection of production issues. • Help create repeatable engineering standards and practices for a data organization that is being built from the ground up. Required Qualifications • Professional experience designing and building production data pipelines. • Strong SQL skills and experience working with relational databases. • Experience ingesting and transforming data from multiple structured or semi-structured sources. • Understanding of data warehouses, data lakes, data marts, data modeling, and modern data-engineering practices. • Experience working with legacy data, incomplete documentation, inconsistent schemas, or disconnected systems. • Ability to investigate data issues and determine root causes across source systems, transformations, and downstream applications. • Experience working with business analysts, architects, infrastructure teams, application teams, and business stakeholders. • Strong documentation and communication skills. • Ability to operate independently in an evolving environment without waiting for every process or requirement to be fully defined. • U.S. citizenship, including the ability to enter the federally governed Bloomington facility. Preferred Qualifications • Semiconductor, high-tech manufacturing, precision manufacturing, aerospace, automotive, medical-device, or other regulated manufacturing experience. • Experience with manufacturing data, production systems, equipment data, quality data, yield analytics, or operational technology. • Experience with data classification, data security, metadata management, row-level security, access management, or customer-data segregation. • Exposure to AI or machine-learning data pipelines. • Experience modernizing older databases or applications into SQL-based or cloud-oriented data environments. • Experience supporting organizations through acquisitions, system consolidation, or data-separation initiatives. Success Profile This role requires an engineer who is resourceful, hands-on, and comfortable working in an environment where the team may only be one or two people deep in a particular discipline. The ideal candidate will not stop when documentation is incomplete or when someone says data cannot be accessed. They will investigate, identify the real constraint, propose practical options, and help move the organization forward. Why This Opportunity The Data Engineer will support advanced semiconductor manufacturing and emerging quantum-computing capabilities. The company is investing in AI initiatives designed to identify production problems earlier, reduce scrap, improve semiconductor yield, and generate substantial measurable returns. This position offers an opportunity to build foundational data capabilities rather than simply maintain an already mature platform.