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Added 23 mins ago
PE
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We use data and analytics technologies, such as artificial intelligence (AI), and automated processing tools, to analyze and process the information you provide to us or third parties in…

Acceldata

Manager, Global Practice and Delivery (Solutions & Services)

Kitchener, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 28, 2026
Posting language: English
Posted: Oct 29, 2026

Original job description

We're looking for a Manager, Global Practice and Delivery to build, lead, and scale a global team of Solutions Consultants and Forward-Deployed Engineers responsible for enterprise implementations, technical consulting, SaaS deployments, and platform migrations.

You'll lead our North American services organization while helping shape global delivery practices that enable customers to successfully deploy, adopt, and realize measurable value from Acceldata's data management and observability solutions.
You'll build a scalable services delivery engine, ensuring customer engagements are delivered on time, within budget, to high-quality standards, and consistently across multiple customers.
You should be equally comfortable discussing data architecture trade-offs with a customer's technical team and coaching Solutions Consultant Or/And , Forward-Deployed Engineers on delivering complex on-premises and SaaS solutions.
We're looking for a forward-thinking leader who combines deep technical delivery expertise with ownership of practice strategy, commercial growth, operational excellence, and organizational capability building.

What You Will Own

Global Team Leadership: Build, hire, coach, and develop a high-performing team of Solutions Consultants and Forward-Deployed Engineers supporting Data & AI Observability and Infrastructure Observability.
Practice Strategy & Growth: Define and execute the professional services strategy, strengthen delivery capabilities, identify opportunities for services growth, and build scalable operating models.
Practice Performance & Leadership Accountability: Own and continuously improve key professional services metrics, including services revenue, gross margin, resource utilization, delivery predictability, customer time-to-value, customer satisfaction, team capability development, and operational scalability.
Customer Engagement: Oversee multiple enterprise customer engagements, ensuring successful delivery, proactive risk management, stakeholder alignment, and measurable business outcomes.

What You Bring

At least 10 years of experience in professional services, software engineering, forward-deployed engineering, or technical consulting, including 5+ years leading customer-facing engineering or delivery teams in a high-growth company
Proven experience running several complex enterprise implementations at once, including planning, resource allocation, risk management, and financial accountability.
Solid understanding of data engineering, distributed systems, cloud platforms, and Kubernetes-based environments. Most important: deep domain expertise in data management, data platforms, or data infrastructure - you can hold your own in conversations about data observability, data quality, spark/kafka processing, kubernetes architectures, or cloud data engineering.
Bachelor’s Or Master's in CS, Engineering, or related field.

Preferred

Strong foundation using AI and automation to improve services delivery
Build a high-performing professional services organisation that delivers enterprise implementations on time, accelerates customer time-to-value, improves delivery efficiency, and drives measurable customer success.
Experience delivering solutions across hybrid-cloud, multi-cloud, and on-premises enterprise environments.

Enterprise data infrastructure and AI are coming together, and Acceldata sits at that point. You will shape our global services and FDE organization, lead experienced technical people, and build delivery practices that scale. You will help customers run their mission-critical data platforms.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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More about this job

Responsibilities

Build and lead a global team of Solutions Consultants and Forward-Deployed Engineers, while shaping scalable professional services practices and operating models. Oversee enterprise customer engagements and services performance, ensuring predictable, high-quality delivery, customer value, and commercial growth.

Requirements

Requires at least 10 years of experience in professional services, software engineering, forward-deployed engineering, or technical consulting, including 5 or more years leading customer-facing engineering or delivery teams. Candidates should have experience managing complex enterprise implementations and strong expertise in data infrastructure, distributed systems, cloud platforms, and Kubernetes; a bachelor's or master's degree in computer science, engineering, or a related field is specified.

Skills

Professional Services Leadership
Team Building and Coaching
Enterprise Implementations
Technical Consulting
SaaS Deployments
Platform Migrations
Data Management
Data Observability
Data Quality
Data Engineering
Distributed Systems
Cloud Platforms
Kubernetes
Resource Allocation
Risk Management
Services Revenue and Gross Margin Management

Visa sponsorship

Not detected in the job text

Keywords

Professional Services
Solutions Consultants
Forward-Deployed Engineers
Enterprise Implementations
Technical Consulting
SaaS
Platform Migrations
Data Management
Data Observability
Infrastructure Observability
Data Quality
Data Engineering
Distributed Systems
Cloud Platforms
Kubernetes
Apache Spark
Apache Kafka
Hybrid Cloud
Multi-Cloud
On-Premises Environments
Services Revenue
Gross Margin
Resource Utilization
Delivery Predictability
Customer Time-to-Value
Customer Satisfaction
Risk Management
Financial Accountability
AI
Automation

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