Technical Delivery Manager

orioninnovation; Edison (NJ); On-site; USD 180,000 - 260,000; Full time

Job summary

Orion Innovation is seeking a Senior Technical Delivery Manager to lead end-to-end delivery of large-scale data, analytics, and AI programs. You will manage a global team across data engineering, software engineering, cloud, DevOps, and analytics, aligning technology with business goals.

The role requires hands-on leadership, enterprise architecture experience, and collaboration with Architecture Review Boards to drive scalable and secure technology decisions.

Qualifications

• Extensive experience leading large, distributed data/AI programs.
• Strong enterprise architecture and governance capabilities.
• Proven ability to translate business objectives into technology roadmaps.
• Hands-on leadership across data, analytics, cloud, and security.
• Global teams across multiple locations and vendors.

Responsibilities

• Lead end-to-end delivery of complex, enterprise-scale data, analytics, and AI programs.
• Manage a globally distributed team across multiple disciplines and time zones.
• Establish governance for scope, schedule, budget, dependencies, quality, risks, resources, and reporting.
• Translate business objectives into actionable technology roadmaps and measurable outcomes.
• Drive deployment automation and DevOps practices across platforms including CI/CD and security scanning.
• Ensure architectures comply with security, privacy, data governance, and regulatory requirements.
• Collaborate with senior leaders to drive technology strategy and value.

Skills

Leadership

Data architecture

Program management

Enterprise data platforms

Cross-functional collaboration

Tools

Databricks

Microsoft Fabric

Azure DevOps

GitHub

Power BI

Job description

Orion Innovation is a premier, award-winning, global business and technology services firm. Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design, and engineering, with a unique combination of agility, scale, and maturity. We work with a wide range of clients across many industries including financial services, professional services, telecommunications and media, consumer products, automotive, industrial automation, professional sports and entertainment, life sciences, ecommerce, and education.

Role Overview

We are seeking an accomplished Senior Technical Delivery Manager to lead the architecture, engineering, and delivery of large-scale data, analytics, and AI platforms. This role requires a rare combination of deep technical expertise, enterprise architecture experience, and proven leadership of globally distributed, multidisciplinary teams. The successful candidate will manage a global organization of approximately 150 resources across data engineering, software engineering, cloud, DevOps, quality engineering, architecture, analytics, AI, and program management. The individual must remain technically hands-on, confidently engage with engineering teams, and partner with enterprise Architecture Review Boards to drive scalable and secure technology decisions.

Key Responsibilities

Technical Delivery and Program Leadership

• Lead the end-to-end delivery of complex, enterprise-scale data, analytics, application, and AI programs.
• Manage a globally distributed team of approximately 150 professionals across multiple disciplines, locations, vendors, and time zones.
• Establish program governance covering scope, schedule, budget, dependencies, quality, risks, resources, and executive reporting.
• Translate business objectives into actionable technology roadmaps, delivery plans, and measurable outcomes.
• Manage multiple concurrent workstreams while maintaining alignment across architecture, engineering, DevOps, security, testing, and operations.
• Drive delivery predictability through effective planning, dependency management, risk mitigation, and outcome-based performance metrics.
• Build strong relationships with senior business leaders, product owners, engineering leaders, and technology partners.

Data and Analytics Platform Engineering

• Provide hands-on technical leadership for large-scale implementations using Databricks and Microsoft Fabric .
• Design and deliver modern enterprise data platforms, including data lakes, lakehouses, warehouses, data pipelines, semantic models, and analytics solutions.
• Guide decisions related to platform architecture, workload design, performance, scalability, security, resiliency, and cost optimization.
• Lead the integration of Microsoft Fabric, Databricks, Power BI, enterprise applications, APIs, and AI capabilities.
• Apply practical knowledge of batch and real-time data processing, medallion architecture, Delta Lake, data modeling, and distributed computing.
• Establish engineering standards and reusable frameworks for data ingestion, transformation, orchestration, quality, observability, and consumption.

Architecture and Technology Governance

• Design and review end-to-end solution architectures spanning data, applications, integrations, analytics, and AI.
• Partner with enterprise architects and Architecture Review Boards to present, defend, and obtain approval for proposed technology solutions.
• Ensure architectures comply with enterprise standards for security, privacy, data governance, resiliency, scalability, and regulatory requirements.
• Lead technical design reviews and challenge engineering teams to develop pragmatic, maintainable, and cost-effective solutions.
• Drive the adoption of reusable architecture patterns, common services, APIs, engineering standards, and technology guardrails.
• Evaluate emerging technologies and provide recommendations based on business value, implementation complexity, risk, and total cost of ownership.

DevOps and Deployment Automation

• Provide hands-on leadership in DevOps using Azure DevOps and GitHub .
• Establish enterprise CI/CD standards across data platforms, applications, APIs, analytics solutions, infrastructure, and AI products.
• Drive full automation of build, testing, security scanning, infrastructure provisioning, deployment, validation, and rollback processes.
• Design and implement blue-green deployment strategies to minimize downtime and reduce production deployment risk.
• Implement infrastructure as code, automated quality gates, branching strategies, release controls, and environment-management practices.
• Establish deployment observability and automated rollback mechanisms to improve release reliability.
• Promote DevSecOps practices by embedding security, compliance, code quality, and vulnerability checks into delivery pipelines.

Data Governance and Strategy

Define and implement enterprise data strategies aligned with business priorities and regulatory r