Senior Technical Delivery Manager Data and AI

Matrix Global•USA,

About The Position

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.

Requirements

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.

Nice To Haves

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.

Responsibilities

Lead End-to-End Data & AI Delivery: Own 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 High-Performing Technical Teams: 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.
Own the Client Relationship: 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.
Drive Technical Delivery Quality: 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.
Support Account Growth & Pre-Sales: 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.