Senior Technical Project Manager, IT (R5279)

About the role

The Senior Project Manager - Technical Delivery & Cross-Functional Execution is an experienced practitioner responsible for driving the end-to-end delivery of complex, technically-led programs across distributed, cross-functional organizations. Operating at the intersection of IT, Product, Data, and Business Operations, this person brings the structure, process rigor, and delivery discipline needed to execute at pace without sacrificing quality or alignment.

Job Description

This role is defined by its breadth: the ability to work fluently across organizational boundaries - aligning engineering squads, product teams, platform and infrastructure groups, and business stakeholders toward shared delivery outcomes. Beyond project execution, this person actively designs and implements the processes, workflows, and tooling that enable teams to operate more effectively and deliver more predictably over time.

Required qualifications

• 5+ years of project or program management experience, with a consistent focus on technical or technology-led initiatives including software development, platform engineering, data or cloud program
• Demonstrable experience working across cross-functional technical teams - IT, Product, Design, Data, DevOps, Infrastructure, and Security - acting as an integrator who drives alignment and delivery across organizational boundaries
• Proven ability to design and implement delivery processes and workflows from scratch or in under-defined environments; able to assess what's needed, build pragmatically, and iterate based on what works
• Strong grasp of the Software Development Lifecycle (SDLC) and technical delivery patterns - including CI/CD pipelines, sprint-based delivery, release trains, and environment management - sufficient to manage delivery risk and engage credibly with engineering teams
• Hands-on experience with agile and hybrid delivery frameworks: Scrum, Kanban, SAFe, or equivalent; comfortable designing the right delivery model for the program rather than applying a single methodology dogmatically
• Strong command of core PM disciplines: scope management, scheduling, risk and issue management, dependency tracking, budget oversight, resource planning, and executive reporting
• Experience with modern project and engineering tooling: Jira, Confluence, Smartsheet, Linear, Notion, or equivalent; able to configure and adapt tooling to support team workflows and leadership visibility
• Excellent facilitation and communication skills - able to run complex multi-team workshops, lead technical planning sessions, and present clearly to both engineering audiences and executive stakeholders
• PMP, PRINCE2, PMI-ACP, or equivalent certification (or demonstrated applied experience at equivalent level); agile certifications welcomed
• High degree of autonomy and self-direction - comfortable operating in ambiguous environments with minimal structural support; able to build structure where it doesn't yet exist
• Experience delivering across multiple technical domains simultaneously - e.g., concurrent platform, data, and product workstreams - with the ability to manage inter-team dependencies at program level
• Background in cloud migration or cloud-native program delivery (AWS, Azure, GCP); understanding of infrastructure-as-code, containerization, and DevSecOps practices and how they affect delivery planning
• Exposure to data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Familiarity with technical architecture review processes; able to participate in architecture decision discussions and understand delivery implications of architectural choices
• Background in regulated technical environments (SOC 2, ISO 27001, HIPAA, GDPR) with experience managing compliance requirements as a delivery constraint
• Experience deploying AI, machine learning, or data science capabilities in a production context; understanding of the unique delivery challenges in probabilistic and iterative ML development
• Prior background as a software engineer, technical business analyst, or solutions architect - bringing ground-level technical credibility that enhances delivery quality and stakeholder trust

Preferred qualifications

• Experience in regulated technical environments (SOC 2, ISO 27001, HIPAA, GDPR)
• Experience deploying AI, machine learning, or data science capabilities in a production context
• Experience with cloud migration or cloud-native program delivery (AWS, Azure, GCP)
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Experience with data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with infrastructure-as-code, containerization, and DevSecOps practices
• Experience with regulatory compliance in technical environments (SOC 2, ISO 27001, HIPAA, GDPR)
• Experience with AI, machine learning, or data science capabilities in a production context
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Experience with data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with infrastructure-as-code, containerization, and DevSecOps practices
• Experience with regulatory compliance in technical environments (SOC 2, ISO 27001, HIPAA, GDPR)
• Experience with AI, machine learning, or data science capabilities in a production context
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Experience with data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with infrastructure-as-code, containerization, and DevSecOps practices
• Experience with regulatory compliance in technical environments (SOC 2, ISO 27001, HIPAA, GDPR)
• Experience with AI, machine learning, or data science capabilities in a production context
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Experience with data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with infrastructure-as-code, containerization, and DevSecOps practices
• Experience with regulatory compliance in technical environments (SOC 2, ISO 27001, HIPAA, GDPR)
• Experience with AI, machine learning, or data science capabilities in a production context
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Experience with data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with infrastructure-as-code, containerization, and DevSecOps practices
• Experience with regulatory compliance in technical environments (SOC 2, ISO 27001, HIPAA, GDPR)
• Experience with AI, machine learning, or data science capabilities in a production context
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Experience with data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with infrastructure-as-code, containerization, and DevSecOps practices
• Experience with regulatory compliance in technical environments (SOC 2, ISO 27001, HIPAA, GDPR)
• Experience with AI, machine learning, or data science capabilities in a production context
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Experience with data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with infrastructure-as-code, containerization, and DevSecOps practices
• Experience with regulatory compliance in technical environments (SOC 2, ISO 27001, HIPAA, GDPR)
• Experience with AI, machine learning, or data science capabilities in a production context
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Experience with data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with infrastructure-as-code, containerization, and DevSecOps practices
• Experience with regulatory compliance in technical environments (SOC 2, ISO 27001, HIPAA, GDPR)
• Experience with AI, machine learning, or data science capabilities in a production context
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Experience with data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with infrastructure-as-code, containerization, and DevSecOps practices
• Experience with regulatory compliance in technical environments (SOC 2, ISO 27001, HIPAA, GDPR)
• Experience with AI, machine learning, or data science capabilities in a production context
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Experience with data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with infrastructure-as-code, containerization, and DevSecOps practices
• Experience with regulatory compliance in technical environments (SOC 2, ISO 27001, HIPAA, GDPR)
• Experience with AI, machine learning, or data science capabilities in a production context
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Experience with data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with infrastructure-as-code, containerization, and DevSecOps practices
• Experience with regulatory compliance in technical environments (SOC 2, ISO 27001, HIPAA, GDPR)
• Experience with AI, machine learning, or data science capabilities in a production context
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Experience with data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with infrastructure-as-code, containerization, and DevSecOps practices
• Experience with regulatory compliance in technical environments (SOC 2, ISO 27001, HIPAA, GDPR)
• Experience with AI, machine learning, or data science capabilities in a production context
• Experience with API-led integration program and the delivery complexity of connecting internal systems, third-party platforms, and data sources across distributed architectures
• Experience with data and analytics program delivery including data platform buildouts, data pipeline implementations, BI and reporting tooling, and data governance workstreams
• Experience with infrastructure-as-code, containerization, and DevSecOps practices
• Experience with regulatory compliance in technical environments (