Data & AI Senior Technical Delivery Manager

Matrix Global•USA,

About The Position

Matrix's Data & AI practice builds and runs 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 own end-to-end delivery on our most strategic accounts — the person the client trusts to make the program land, and the person our engineers trust to clear the road ahead of them. This is a hands-on leadership role. You will not be writing production code day to day, but you will be technical enough to challenge an architecture decision, read a Databricks job failure and know what it means, and hold your own in a design review with a client's Chief Data Officer.

Requirements

10+ years in technology delivery, with at least 5 years managing complex data or analytics programs.
Consulting or professional services background — you understand utilization, margin, SOWs, change orders, and the difference between a client and an employer.
Hands-on working knowledge of Snowflake and/or Databricks in production environments (required). You should be able to speak credibly about warehouse vs. lakehouse architecture, Delta/Iceberg, Unity Catalog or Snowflake governance, workload optimization, and platform cost drivers.
Familiarity with the surrounding modern stack: ELT and orchestration (dbt, Airflow, ADF, Fivetran), cloud platforms (Azure, AWS, or GCP), BI and semantic layers (Power BI, Tableau), and CI/CD for data.
Demonstrated experience leading distributed onshore/offshore delivery teams.
Track record of direct executive-level client engagement, including at least one program you personally recovered or turned around.
Strong command of Agile and hybrid delivery methods, and the judgment to know which one a given client actually needs.
Excellent written and verbal communication; comfortable presenting to a room of senior stakeholders.
Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.

Nice To Haves

Experience in one or more of: financial services, CPG, retail, or construction/AEC.
Exposure to Dataiku, MLOps tooling, or GenAI and agentic solution delivery.
Prior background as a data engineer, BI developer, or solution architect before moving into delivery leadership.
Certifications: Databricks, Snowflake (SnowPro), cloud platform (Azure/AWS/GCP), PMP, or SAFe.
Experience with data governance, data quality, or regulatory-driven programs (privacy, AML, model risk).
Ability to travel to client sites as needed (typically [X]%).

Responsibilities

Own delivery: Lead multi-workstream Data & AI programs from kickoff through steady-state, with accountability for scope, schedule, margin, quality, and client outcomes.
Build and maintain delivery plans, RAID logs, sprint cadences, and governance rhythms that hold up under executive scrutiny.
Run status reporting and steering committees that surface risk early rather than explaining it late.
Manage change control: identify scope drift, quantify impact, and negotiate change orders without damaging the relationship.
Lead teams: Lead blended onshore/offshore teams of 8–25 engineers, architects, analysts, and consultants across multiple concurrent workstreams.
Set delivery standards and hold the team to them — code review discipline, documentation, environment hygiene, DevOps practices.
Coach and develop team members; own staffing plans, ramp-up, and performance feedback in partnership with practice leadership.
Resolve technical and interpersonal blockers quickly, escalating only what genuinely needs escalating.
Own the client relationship: Serve as the primary day-to-day point of contact for client program sponsors, data leaders, and business stakeholders.
Translate between business intent and technical reality in both directions — and say the hard thing when a timeline or an approach won't work.
Run executive-level communication: QBRs, KPI reviews, escalation handling, and recovery plans when a program is off track.
Protect client satisfaction as a measurable outcome, not a feeling.
Drive technical quality: Provide oversight, with practice architects, on solution design across Snowflake, Databricks, and the surrounding modern data stack.
Ensure delivery follows sound patterns for data modeling, pipeline orchestration, governance, security, cost management, and production support.
Bring judgment on build vs. buy, platform trade-offs, and technical debt — and make sure those decisions are documented and defensible.
Oversee delivery of AI/ML and GenAI workloads, including model lifecycle, evaluation, and responsible-AI considerations where applicable.
Grow the account: Identify and shape follow-on opportunities within existing accounts; contribute to SOWs, estimates, and staffing models.
Support pre-sales as the delivery voice in pursuits — solution shaping, effort estimation, risk assessment, and client presentations.
Contribute to practice assets: delivery playbooks, accelerators, reusable frameworks, and lessons-learned.