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Data Architect

Employment Type: Six-Month Contract-to-Hire

Location: Northern Milwaukee, WI area – Hybrid, three days onsite per week

This position is intended to convert to full-time employment after approximately six months. We are seeking candidates who are genuinely interested in a long-term opportunity—not a contract-only engagement.

Position Overview

We are seeking a Data Architect to help a growing manufacturing organization define the future of its enterprise data platform.

The initial focus will be evaluating and selecting the right technologies and architecture for the organization’s evolving data environment. This includes assessing Snowflake versus Databricks, streaming capabilities, data catalogs, data-quality tools, and how these technologies will integrate with the broader enterprise ecosystem.

This individual will partner closely with enterprise architecture, data engineering, business leaders, and other technical stakeholders to establish a scalable data strategy. The resulting roadmap will support advanced analytics, predictive maintenance, operational decision-making, automation, and future AI and machine-learning capabilities.

The ideal candidate is both strategic and technically credible—someone who can assess competing technologies, make informed recommendations, communicate tradeoffs, and translate business needs into a practical enterprise data roadmap.

Key Responsibilities

• Evaluate Snowflake, Databricks, and related Azure services to help define the organization’s future data-platform strategy.
• Assess platform capabilities, limitations, costs, scalability, integration requirements, and long-term business fit.
• Evaluate streaming technologies, data catalogs, data-quality tools, and supporting architecture components.
• Define how selected technologies will integrate with the organization’s broader application, ERP, manufacturing, cloud, and analytics environments.
• Partner with enterprise architecture to establish the future-state data architecture and implementation roadmap.
• Design scalable patterns for data ingestion, integration, storage, transformation, streaming, and consumption.
• Establish architectural standards supporting data quality, governance, lineage, metadata management, security, and accessibility.
• Help shape solutions for predictive maintenance, advanced analytics, operational intelligence, and real-time decision-making.
• Develop the architectural foundation needed to support future AI and machine-learning capabilities.
• Lead technology evaluations, architecture reviews, and strategic planning sessions.
• Present recommendations, tradeoffs, and architectural direction to technical teams, business leaders, and executives.
• Collaborate with data engineers, analytics teams, enterprise architects, business stakeholders, and external technology partners.

Required Qualifications

• Strong enterprise data architecture or modern data-platform architecture experience.
• Hands-on knowledge of Snowflake, Databricks, and Microsoft Azure.
• Experience evaluating data technologies and making platform or tool-selection recommendations.
• Experience designing modern cloud-based data platforms and enterprise integration strategies.
• Strong understanding of data lakes, data warehouses, lakehouse architecture, data modeling, APIs, ETL/ELT, and data integration.
• Experience with streaming or event-driven data architecture.
• Knowledge of data catalogs, data-quality tools, metadata management, lineage, governance, and security.
• Ability to connect technical architecture decisions to business needs and long-term organizational strategy.
• Strong communication skills with the ability to influence technical, business, and executive stakeholders.
• Ability to work onsite in Northern Milwaukee area, three days per week.
• Genuine interest in converting to a long-term, full-time position following the initial six-month contract period.

Preferred Qualifications

• Experience supporting manufacturing, supply chain, industrial operations, or an ERP-driven organization.
• Experience with predictive maintenance, Industrial IoT, operational analytics, or real-time manufacturing data.
• Experience helping an organization compare Snowflake and Databricks or define a modern data-platform roadmap.
• Exposure to AI, machine learning, predictive analytics, or the architecture required to support these capabilities.
• Experience with Azure Data Services, Python, PySpark, SQL, Kafka, CDC, Power BI, Tableau, or Alteryx.
• Experience leading data-modernization or enterprise digital-transformation initiatives.

Why Consider This Opportunity?

This is an opportunity to influence major enterprise technology decisions rather than simply maintain an established environment. You will help select the organization’s future data platforms, shape its architecture roadmap, and build the foundation for advanced analytics, predictive maintenance, and AI.