Director of Data and Analytics

Department: IT    Location: Remote, USA

About Trilon

Trilon was formed with the vision of building the next Top 20 infrastructure consulting firm in North America by bringing together some of the nation’s best infrastructure consulting firms, focused on delivering practical and sustainable infrastructure solutions. Trilon is backed by Alpine Investors, a PeopleFirst Private Equity Firm. Trilon currently comprises 5,500+ staff across the US.

About the role

Trilon is building a supercharged, technology-enabled future for our people and partners. The Director of Data & Analytics plays a critical role in that mission by owning the accuracy, consistency, and delivery of everything the data and analytics organization produces. You lead a team of data engineers and data analysts, ensuring that every contributor operates with clarity, consistency, and a high bar for quality. This is a player-coach leadership role: you are not building production pipelines or reports day to day, but you stay close enough to the work to guide architecture and modeling decisions, identify risks early, and maintain credibility with the engineers and analysts you lead.

You set the culture, delivery expectations, and quality standards that define what it means to ship trusted data and insight at Trilon. You work closely with engineering, product, and business leadership to ensure alignment between priorities, data design, and delivery capacity. You serve as the primary escalation point for data and analytics challenges and are accountable for ensuring that teams deliver a reliable data foundation without accumulating debt that slows future decisions.

Responsibilities

• Data & Analytics Leadership and Organizational Ownership
  • Lead a team of data engineers and data analysts
  • Set expectations for data and analytics performance, delivery, and quality
  • Establish and maintain a strong data culture focused on accountability and execution
  • Serve as the escalation point for technical, delivery, and team-related challenges
• Data & Analytics Operating Model and Standards
  • Define and govern the operating model across data engineering and analytics
  • Establish standards for pipelines, semantic modeling, metric definition, and reporting
  • Define and enforce code review, testing, and release standards
  • Drive continuous improvement in processes, tools, and practices
• Delivery Execution and Velocity
  • Own delivery timelines, throughput, and capacity planning
  • Ensure alignment between business priorities and data and analytics execution
  • Identify and remove blockers that impact team velocity
  • Balance speed and quality to ensure sustainable delivery
• Data Platform and Analytics Architecture
  • Partner with the Principal Solutions Architect and Lead Data Engineer on standards
  • Stay close to technical decisions to identify risks and ensure sound design
  • Support leads in making strong architecture, modeling, and implementation choices
  • Ensure technical debt is managed and does not hinder future development
• Data Governance, Quality, and Security
  • Own data quality, lineage, and governance across pipelines, models, and reports
  • Establish cataloging, classification, and access standards (e.g., Microsoft Purview)
  • Ensure consistent metric definitions and a single source of truth
  • Ensure appropriate data security and access governance
• AI-Enabled Data and Analytics
  • Prepare data pipelines and models for AI, machine learning, and generative AI use cases
  • Enable high-quality data inputs for copilots, agents, and intelligent applications
  • Deliver reporting on adoption, ROI, and impact of AI and Digital program initiatives
  • Leverage AI tooling to improve data and analytics productivity
• Cross-Functional Collaboration
  • Work with the VP of Data and Engineering on data and analytics strategy and growth
  • Partner with engineering and product leaders to align on data definitions and priorities
  • Collaborate with business and program leadership to deliver decision-driving insights
  • Ensure alignment between data and analytics execution and broader program goals
• Talent Management and Team Development
  • Hire, develop, and retain data engineers, data analysts, and team leads
  • Own headcount planning, onboarding quality, and performance management
  • Oversee staff augmentation to the same standards as internal teams

Requirements

• 10+ years of experience in data engineering, analytics, or data platform roles
• 5+ years in data or analytics leadership roles, managing teams or functions
• Proven experience leading data and analytics teams across multiple business units
• Strong understanding of modern data and analytics practices, including agile delivery
• Experience defining and operating data and analytics processes at scale
• Ability to make informed data and architectural decisions
• Experience managing data and analytics capacity, delivery timelines, and prioritization
• Strong people-management skills, developing senior data engineers and analysts
• Experience working closely with engineering, product, and business functions
• Familiarity with the Microsoft data stack, Purview, and AI-powered systems is preferred
• Experience managing external or staff augmentation data resources is a plus
• Strong communication skills across technical and non-technical stakeholders
• Ability to operate in a fast-paced, evolving environment with multiple priorities
• Experience in AEC, engineering, or professional services environments is a strong advantage
• Ability to travel up to 30% across the United States

Pay

The base salary range for this role is $234,000 - $260,000 per year. Final compensation will be determined based on factors such as experience, skills, qualifications, internal equity, and geographic location.