Department Manager, Operating Model & Strategy - Data & AI Function

Burns & McDonnell

Houston (TX)

On-site

USD 180,000 - 280,000

Full time

5 days ago

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Job summary

Burns & McDonnell seeks a Director of Operating Model & Strategy to own the Enterprise Data & AI roadmap and the operating model that executes it. Reporting to the Managing Director, Data & AI, this leader ensures business engagement, engineering and AI delivery, portfolio execution, governance, capacity, and performance as one function.

The role drives strategy into disciplined execution, leads cross-functional teams across multiple locations, and partners with Finance on value realization and

Qualifications

Bachelor’s degree and 15+ years in enterprise strategy/operations.
Experience running complex cross-functional operations and converting enterprise strategy into roadmaps, portfolios and cadences.
Experience leading program/portfolio management, business analysis, agile/Scrum, or delivery-management capabilities.
Proven ability to hire and develop top talent across locations.
Strong understanding of Data & AI delivery lifecycles and governance, adoption, and value realization.
Experience with enterprise OKRs/KPIs and executive reporting.
Experience with Finance involvement in investment governance.
Experience in engineering, construction, EPC, professional services or federated enterprise.

Responsibilities

Own and evolve the Enterprise Data & AI Strategy and 1–3 year roadmap, aligned to business priorities.
Translate strategy into annual operating priorities, OKRs, KPIs, initiatives, investment requirements, and owners.

Skills

Executive communication

Business acumen

Data & AI delivery

Transformation leadership

OKRs KPIs

Finance partnership

AI governance

Cross-functional leadership

Talent leadership

Industry experience

Education

Bachelor’s degree in business, engineering, computer science

Job description

Description

The Director, Operating Model & Strategy owns and drives the Enterprise Data & AI roadmap and the operating model that executes it. Reporting to the Managing Director, Data & AI, this leader ensures business engagement, engineering and AI delivery, portfolio execution, governance, capacity, and performance work as one cohesive function. The Department Manager is accountable for tracking and reporting portfolio value, delivery, and P&L impact, and for turning strategy into a disciplined, measure able execution system.

Key Responsibilities

Strategy & Roadmap

Own and continuously evolve the Enterprise Data & AI Strategy and 1–3 year roadmap, aligned to business priorities and the Business Enablement strategy.
Translate strategy into annual operating priorities, OKRs, KPIs, initiatives, investment requirements, and accountable owners.

Operating Model & Execution

Own and run the Data & AI operating model and its cadences, ensuring clear communication, coordination, decision‑making, escalation, and execution across teams.
Lead the Business Analysis, Scrum/Agile, and Program/Portfolio Management capabilities and deploy them to priority work.
Drive continuous improvement so operating mechanisms become simpler, faster, more transparent, and scalable as the function matures.
Hire, develop, and retain top talent across Business Analysis, Scrum/Agile, and Program/Portfolio Management, build enduring capability, and lead teams across multiple locations.

Portfolio, Value & Performance

Own the Shared Business Backlog and portfolio process: prioritization, sequencing, dependencies, milestones, risk, and an integrated capacity view.
Accountable for tracking portfolio value, delivery, and P&L impact; establish a consistent performance system covering value, delivery, adoption, capacity, risk, and operating health.
Own Data & AI executive reporting, including value validation in partnership with Finance.

Governance

Operate the Data & AI Operating Committee (DOC) and Data Executive Operating Committee (DEOC) routines so forums receive decision‑quality information and resolve trade‑offs at the right level.
Orchestrate AI governance across Business Enablement Strategy, Data & AI, IT, Architecture, Security, Legal, Risk, and business stakeholders, maintaining clear decision rights, workflows, and control visibility.

Partnerships & Resources

Partner with the Director, Business Data Engagement so qualified demand, sponsor commitments, and adoption requirements are reflected in portfolio decisions.
Partner with the Director, Data Engineering & AI so priorities are technically feasible, capacity‑backed, sequenced, and delivered to common standards.
Coordinate workforce, vendor/SI, budget, and capacity planning with the Managing Director and enterprise partners; surface friction, constraints, unclear ownership, and delivery risks early and drive resolution.

Stakeholder Influence

Influence executives and governance forums to make timely, evidence‑based trade‑off and investment decisions.
Align the three Data & AI leadership pillars and enterprise partners (IT, Security, Legal, Risk, Finance) through influence rather than positional authority.
Hold the function accountable to its commitments (priorities, milestones, value) and make delivery performance visible to leadership.
Build a high‑trust culture where escalation, constructive challenge, and course correction are routine.

What Success Looks Like (First 12 Months)

Roadmap: Enterprise Data & AI Strategy and 1–3 year roadmap approved by the Managing Director and executive sponsors, with annual OKRs and KPIs cascaded to named owners.
Portfolio: A single Shared Business Backlog and integrated capacity view in use, with prioritization decisions made through the portfolio process.
Reporting: A baseline performance dashboard reviewed monthly with the Managing Director, covering value, delivery, adoption, capacity, risk, and operating health.
Value: Value and P&L impact tracked for priority initiatives and validated with Finance, with a clear line from investment to realized benefit.
Governance: DOC/DEOC operating on a predictable cadence; decisions and escalations resolved on time with documented decision rights.
Delivery: On‑time delivery against committed milestones, with cross‑team risks and capacity conflicts identified early. Targets to be set with the Managing Director at the start of the role.

Qualifications

Bachelor’s degree in business, engineering, computer science, or a related field from an accredited program, and a minimum of 15 years of related professional experience across enterprise strategy execution, operating models, portfolio/program management, data/technology transformation, or business operations, including significant leadership responsibility.
Demonstrated experience running complex cross‑functional operations and converting enterprise strategy into roadmaps, portfolios, operating cadences, and measurable execution.
Experience leading program/portfolio management, business analysis, agile/Scrum, or comparable delivery‑management capabilities.
Proven ability to hire and develop top talent and to lead teams across multiple locations.
Strong understanding of Data & AI delivery lifecycles and how business demand, engineering capacity, governance, adoption, and value realization connect.
Experience establishing enterprise OKRs/KPIs, executive reporting, portfolio health measures, and risk/dependency management.
Strong executive communication, facilitation, and influence skills in a matrixed environment, with the ability to create clarity from ambiguity and build accountability without unnecessary bureaucracy.
Strong business and financial acumen, including investment prioritization, workforce/capacity planning, vendor management, and value realization, with a track record of measurable business impact from data.
Experience in engineering, construction, EPC, professional services, or another federated, project‑centric enterprise preferred.
Experience establishing or operating enterprise Data & AI strategy, governance, and operating models preferred.
Experience with AI governance, responsible AI frameworks, enterprise technology governance, or cross‑functional risk/control models preferred.
Experience partnering with Finance on investment governance and benefits/value validation preferred.
Experience leading transformation across autonomous business units while preserving local agility and enterprise standards preferred.