Senior Technical Delivery Manager Data and AI

About the role

Matrix's Data & AI practice designs, builds, and operates modern data platforms and AI solutions for enterprise clients across financial services, CPG, retail, and construction. We are looking for a Senior Technical Delivery Manager to lead end-to-end delivery for some of our most strategic client engagements. You will be the person clients rely on to ensure programs deliver measurable business outcomes — and the person engineering teams rely on to remove obstacles and keep delivery moving. This is a hands-on technical leadership role. You will not be expected to write production code every day, but you should be technically strong enough to challenge architecture decisions, understand a Databricks job failure, evaluate platform trade-offs, and confidently participate in technical design discussions with senior client stakeholders, including Chief Data Officers and technology leaders.

Responsibilities

• Lead end-to-end delivery of complex, multi-workstream Data & AI programs from kickoff through production and steady state.
• Maintain accountability for scope, schedule, budget/margin, quality, risks, and client outcomes.
• Build and manage detailed delivery plans, RAID logs, sprint cadences, dependencies, and governance processes.
• Lead program status meetings and executive steering committees, proactively identifying risks and creating mitigation plans.
• Manage scope and change control, including identifying scope creep, assessing business and financial impact, and negotiating change orders with clients.
• Lead distributed onshore/offshore teams of 8–25+ engineers, architects, data professionals, and consultants across multiple workstreams.
• Establish delivery standards around engineering quality, documentation, code reviews, DevOps, environment management, and production readiness.
• Own staffing and ramp-up plans in partnership with practice leadership.
• Coach, mentor, and develop team members while providing meaningful performance feedback.
• Remove technical, delivery, and interpersonal blockers quickly and escalate issues when executive intervention is genuinely required.
• Serve as the primary day-to-day delivery leader for client executives, data leaders, technology stakeholders, and business sponsors.
• Translate business objectives into practical technical and delivery strategies — and communicate technical realities in clear business terms.
• Build trusted relationships with senior stakeholders and provide transparent, fact-based communication.
• Lead executive-level meetings, including QBRs, KPI reviews, steering committees, escalations, and recovery plans.
• Take ownership when programs go off track and lead structured recovery efforts to bring them back to plan.
• Make client satisfaction and measurable business outcomes a core delivery KPI.
• Partner with solution architects to oversee architecture and technical delivery across Snowflake, Databricks, and the modern data stack.
• Ensure solutions follow strong engineering practices across: data architecture and modeling; data pipelines and orchestration; data governance and security; performance and workload optimization; cloud infrastructure; cost management; production support and reliability.
• Evaluate and guide build-vs-buy decisions, platform choices, technical debt, and architectural trade-offs.
• Ensure key technical decisions are documented, communicated, and defensible.
• Oversee delivery of AI/ML and GenAI solutions, including model lifecycle management, evaluation, production readiness, and responsible AI considerations where applicable.
• Identify and help shape follow-on opportunities and expansion within existing accounts.
• Contribute to proposals, SOWs, estimates, delivery approaches, staffing models, and commercial planning.
• Serve as the delivery and technical voice during pre-sales pursuits and client presentations.
• Partner with sales and practice leadership to assess delivery risks and ensure commitments are realistic and achievable.
• Contribute to reusable delivery playbooks, accelerators, frameworks, and lessons learned across the Data & AI practice.

Required Qualifications

• 10+ years of experience in technology delivery, consulting, or professional services, including at least 5 years leading complex data, analytics, or AI programs.
• Experience working within a consulting or professional services environment, with a strong understanding of utilization, margins, SOWs, change orders, and commercial delivery.
• Hands-on working knowledge of Snowflake and/or Databricks in production environments.
• Ability to confidently discuss modern data architecture concepts, including: data warehouse vs. lakehouse architecture; Delta Lake and/or Apache Iceberg; Unity Catalog and/or Snowflake governance; data workload optimization; cloud architecture and platform cost drivers.
• Working knowledge of modern data technologies such as dbt, Airflow, Azure Data Factory, Fivetran, and comparable ELT/orchestration platforms.
• Experience with at least one major cloud platform: Azure, AWS, or GCP.
• Familiarity with Power BI, Tableau, semantic layers, and data CI/CD practices.
• Demonstrated success leading distributed onshore/offshore technical teams.
• Strong executive presence and experience engaging directly with C-suite and senior technology/data leaders.
• Proven experience recovering or turning around at least one challenging or at-risk program.
• Strong command of Agile and hybrid delivery methodologies, with the judgment to adapt the delivery model to the client and engagement.
• Excellent written, verbal, presentation, and stakeholder-management skills.
• Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.

Preferred Qualifications

• Experience working with clients in financial services, CPG, retail, or construction/AEC.
• Exposure to Dataiku, MLOps platforms, GenAI, or agentic AI solutions.
• Previous experience as a Data Engineer, BI Developer, Data Architect, or Solution Architect before transitioning into delivery leadership.
• Experience with data governance, data quality, privacy, AML, model risk, or other regulatory-driven programs.
• Relevant certifications such as: Databricks, Snowflake SnowPro, Azure/AWS/GCP, PMP, SAFe.
• Willingness and ability to travel to client sites as needed.