Data Architect

Founded in 1978, CAMP Facility Services offers a vibrant work environment and a strong commitment to quality, accessible support, and holistic project management. We prioritize relationships with clients and staff alike, treating everyone like family.

Specializing in commercial construction and building maintenance, we serve construction managers, property managers, and building owners across diverse sectors. Our mission emphasizes partnership, continuous improvement through teamwork and education, and exceeding expectations to build lasting relationships based on respect and professionalism.

The Data Architect plays a key leadership role in designing and managing the company's enterprise data architecture to enable smarter, faster, and more efficient project execution across all renovation and restoration operations. This position oversees the data team and develops scalable cloud-based data solutions that integrate project management, financial, and operational systems — empowering field and corporate teams with real-time insights into cost, schedule, and performance.

The Data Architect partners with business leaders, project managers, and IT to ensure data is accurate, secure, and actionable. This role will define the company's data strategy, improve data accessibility across platforms such as Procore, Sage Intacct, Salesforce and Microsoft Power BI, and drive automation initiatives that strengthen project delivery, forecasting, and profitability.

Why join our CAMP?

Our employees are encouraged to take advantage of an array of benefits and opportunities, including:

• Health Benefits - Medical, Dental & Vision
• 401K and Company Match Benefits
• Paid Holidays, Vacation, and Personal Time Off
• 1 Paid Day Off for Community Service
• Employee Referral Bonuses
• Tuition Reimbursement
• Advancement Opportunities

How you will contribute to our TEAM:

• Lead and manage the daily operations of the data team, promoting collaboration between IT, accounting, operations, and project management departments.
• Design and implement a modern data architecture to centralize information from construction management systems (Procore, Sage Intacct, Salesforce, and other SaaS applications).
• Develop and maintain data pipelines and ETL/ELT workflows for project cost tracking, schedule performance, and operational analytics.
• Integrate data from field applications, ERP systems, and job cost reports into a unified warehouse or data lake for analytics and dashboarding.
• Implement and manage data governance policies that ensure data accuracy, consistency, and security across departments.
• Develop and maintain a Master Data Management (MDM) framework for clients, vendors, projects, and cost codes.
• Collaborate with finance and project controls teams to enhance cash flow visibility, forecasting accuracy, and budget performance analytics.
• Automate data flows and integrations through APIs and tools like Fabric Pipelines/Notebooks, Power Automate (RPA), reducing manual data entry and reconciliation.
• Establish and maintain data documentation, security standards, and naming conventions consistent with company policy.
• Evaluate emerging AI and automation technologies (e.g., predictive cost modeling, schedule optimization, risk detection) and recommend implementation strategies.
• Mentor data engineers and analysts, providing technical leadership and ensuring best practices in data modeling and system integration

Our Requirements:

• 10+ years of experience in data architecture, data engineering, or business intelligence, with at least 3 years in a leadership or management role.
• Strong expertise with Microsoft Azure data services (Fabric, Synapse, Data Factory, SQL Server) and Power BI.
• Experience integrating Procore, Sage Intacct, Salesforce and other construction industry software through APIs or middleware.
• Deep understanding of data modeling, data warehouse/lakehouse architectures, ETL/ELT processes, and automation frameworks.
• Advanced proficiency in SQL (T-SQL preferred) and Python or C# for data transformation and integration scripting.
• Knowledge of data governance, data quality, security, and metadata management best practices.
• Familiarity with AI/ML methodologies and Robotic Process Automation (RPA) for operational efficiency.
• Hands-on experience with BI tools, dashboard design, and data performance optimization.
• Strong understanding of financial and operational metrics relevant to construction, including project profitability, WIP reporting, and earned value analysis.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or a related field.
• Experience working within construction, engineering, or real estate development industries.
• Knowledge of NoSQL databases (Cosmos DB, MongoDB) and API management tools.
• Experience with data catalog and governance platforms (Microsoft Purview, Collibra, Alation).
• Understanding of forecasting, scheduling, and asset lifecycle data models in construction.

Core Competencies

• Strong analytical and strategic mindset with the ability to connect data insights to business outcomes.
• Excellent communication skills — able to bridge the gap between technical data teams and project operations.
• Proven leadership ability to manage and mentor cross-functional data and analytics teams.
• Highly organized and detail-oriented, with a focus on quality and data accuracy.
• Ability to manage multiple priorities and meet deadlines in a fast-paced, project-driven environment.
• Commitment to continuous improvement and staying current with emerging data technologies.

Success in this Role Will Be Measured By

• Improved data accuracy, integration, and accessibility across project management and financial systems.
• Increased automation in data workflows, reducing manual entry and reconciliation.
• Enhanced visibility into project performance (cost, schedule, and profitability).
• Adoption of governed, self-service analytics across business units.
• Reduced delays in financial and operational reporting cycles.
• Implementation of scalable data frameworks that support future AI and predictive analytics initiatives.

CAMP is and EOE, compensation is DOE