Software Architect, Data Engineer, Data Analyst

ABOUT US

Davis Technology Management is a successful technology company in the IT staffing, Technology Consulting and IT Managed Services sector. Our focus is crafting technical and staffing solutions that empower businesses and foster growth. Our foundation is built on a commitment to our Core Values, and a team dedicated to bridging the gap between innovative IT solutions and businesses seeking to navigate the complexities of the digital age.

At the heart of everything we do, we’re dedicated to exceeding expectations and creating RAVING FANS both within our internal team and amongst our clients.

We are seeking a senior-level Software Architect specializing in Data & Analytics to lead the design and implementation of a modern enterprise analytics platform. This individual will define the organization’s target-state data architecture, establish scalable data pipelines and reporting frameworks, and create the foundational standards that enable reliable, self-service analytics across the business.

This is a strategic and hands-on role responsible for simplifying a complex data landscape, optimizing tooling and costs, and building a scalable Lakehouse-style architecture supporting both operational and analytical reporting. The architect will work closely with engineering teams and business stakeholders to ensure data is structured, governed, and delivered in a way that supports meaningful decision-making.

In addition to architecture leadership, the role includes hands‑on prototyping, defining governance and data quality standards, mentoring teams, and guiding the organization toward a mature, scalable, and cost‑effective analytics capability.

• Define enterprise data architecture, pipelines, and reporting layers
• Establish scalable Lakehouse / medallion data models (bronze, silver, gold)
• Simplify and rationalize existing analytics tools and platforms
• Develop long‑term roadmap aligned with business goals

• Build reference implementations and architectural blueprints
• Prototype solutions and guide development teams
• Ensure scalability, performance, and maintainability

• Implement data governance, quality, and security frameworks
• Establish cataloging, naming conventions, and documentation standards
• Enable self‑service analytics while maintaining data integrity

• Partner with business leaders to support strategic reporting needs
• Mentor engineering teams on architecture best practices
• Translate complex technical concepts into clear business value

• Bachelor’s degree in Computer Science, Engineering, or related discipline
• 7–10+ years of experience in software architecture with strong focus on enterprise data and analytics platforms
• Proven experience designing and implementing modern data architectures, including ETL/ELT pipelines, data warehousing, and Lakehouse / medallion patterns
• Strong data modeling expertise across both operational (normalized) and analytical (dimensional / star schema) models
• Experience building semantic layers and enabling self‑service reporting, preferably with Power BI
• Hands‑on experience with enterprise data platforms such as Microsoft Fabric, AWS data services, or equivalent
• Experience implementing data governance frameworks, including data quality, lineage, cataloging, and stewardship
• Excellent communication skills with the ability to engage both technical teams and business stakeholders
• Strategic mindset with the ability to design scalable, long‑term analytics solutions aligned to business decision‑making

• Cloud or data certifications (AWS Solutions Architect, AWS Data Analytics Specialty, Microsoft Fabric, Azure Data Engineer, etc.)
• Experience working within AWS or Microsoft Fabric environments
• Familiarity with Power BI Copilot or natural language analytics capabilities
• Experience supporting logistics, transportation, or supply chain analytics environments
• Broader experience across cloud architecture or enterprise application architecture

This role will define and establish the enterprise data architecture standards, patterns, and governance framework used across the organization.

• Establish scalable and cost‑efficient analytics architecture
• Define architectural standards, best practices, and implementation patterns
• Guide engineering teams through architecture adoption
• Lead architecture reviews and strategic platform decisions
• Enable a self‑service analytics environment while maintaining strong governance

This individual will play a key role in advancing the organization’s overall data maturity and analytics capabilities.

• Cloud‑based enterprise data environment
• Microsoft Power BI with Copilot capabilities
• Microsoft Fabric and/or AWS data services
• Relational databases and cloud storage platforms
• Mix of existing ETL, replication, and pipeline technologies undergoing modernization