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Added 4 mins ago
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Lead Quality Assurance Developer
OpenText
Waterloo, ON
- Full-time
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Added 4 mins ago
RD
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Added 1 hour ago
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Added 2 hours ago
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Added 2 hours ago
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EXL

Senior Engagement Manager

Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Dec 13, 2026
Experience: 12-18 years of experience across analytics, data, AI, digital transformation, management consulting, or technology-enabled business transformation.
Posting language: English
Posted: Oct 27, 2026

Original job description

Key Responsibilities

Client Leadership & Executive Engagement

Build trusted relationships with client executives and senior business, data, digital, operations, engineering, supply chain, and technology leaders.

Independently lead steering committees, quarterly business reviews, transformation workshops, roadmap discussions, and executive working sessions.

Translate business priorities and operational challenges into analytics, data, AI, and digital transformation initiatives.

Present complex findings, recommendations, and investment cases through clear executive storytelling and data-driven narratives.

Act as the primary client-facing leader for strategic engagements and maintain alignment across client and EXL leadership teams.

Manufacturing & Automotive Transformation

Lead analytics and AI programs across manufacturing operations, supply chain, procurement, logistics, production planning, demand planning, and inventory optimization.

Shape solutions for quality analytics, warranty analytics, connected manufacturing, engineering analytics, plant performance, digital manufacturing, and industrial AI.

Identify high-value use cases supporting throughput, productivity, quality, cost, service, working capital, asset performance, safety, and sustainability outcomes.

Connect business priorities with practical operating-model, process, data, analytics, and technology interventions.

Data & AI Transformation

Define enterprise analytics and AI strategies, transformation roadmaps, and prioritized use-case portfolios.

Lead data-platform modernization, cloud migration, data engineering, data management, governance, quality, integration, and analytics enablement initiatives.

Guide solutions across descriptive, predictive, prescriptive, optimization, simulation, forecasting, root-cause analysis, and operational intelligence use cases.

Enable machine learning, generative AI, agentic AI, and decision-intelligence solutions through scalable and governed data foundations.

Partner with architects, engineers, data scientists, and business teams to ensure solutions are secure, scalable, adoptable, and tied to measurable outcomes.

Solutioning & Business Development

Lead solution design and consulting engagements for both focused initiatives and complex multi-workstream transformation programs.

Own or contribute to proposals, RFPs, RFIs, statements of work, executive pitches, and deal-shaping discussions.

Develop transformation roadmaps, delivery approaches, staffing models, workplans, effort estimates, cost estimates, assumptions, dependencies, and risks.

Present differentiated solutions to executive stakeholders and guide opportunities from qualification through closure and transition to delivery.

Collaborate with sales, account, industry, capability, architecture, and delivery leaders to expand strategic client relationships.

Account Growth & Commercial Leadership

Provide independent leadership for client portfolios and engagements valued up to $10M-$15M annually.

Develop account growth strategies and identify cross-sell and upsell opportunities across analytics, data, AI, GenAI, and transformation services.

Build executive relationships across multiple client functions and create a forward-looking opportunity pipeline.

Apply strong financial and commercial discipline to scope, pricing, margins, staffing, utilization, and delivery commitments.

Delivery Leadership

Provide executive oversight across multiple programs and workstreams from discovery through implementation and managed delivery.

Establish program governance, monitor risks and dependencies, and drive timely resolution of delivery and stakeholder issues.

Ensure high-quality outcomes, strong customer satisfaction, effective resource planning, and disciplined performance management.

Mentor delivery managers, engagement leads, solution architects, analytics leaders, and technical teams.

Capability Building & Innovation

Build and scale Manufacturing Analytics, Data, AI, and GenAI capabilities, solutions, and reusable assets.

Develop industry-specific frameworks, maturity assessments, accelerators, reference architectures, case studies, and points of view.

Contribute to hiring, team building, talent development, competency planning, and communities of practice.

Drive thought leadership and innovation across smart manufacturing, connected operations, digital thread, digital twins, industrial data, and AI-enabled decision-making.

Qualifications

Required Experience & Qualifications
- 12-18 years of experience across analytics, data, AI, digital transformation, management consulting, or technology-enabled business transformation.
- At least five years of client-facing leadership experience across analytics, data, AI, or transformation engagements.
- Proven ability to independently manage strategic client relationships and portfolios or engagements valued up to $10M-$15M annually.
- Experience leading executive discussions, steering committees, transformation workshops, roadmap development, and solution presentations.
- Demonstrated ability to create compelling executive stories that connect data and analytical insights to business priorities and financial outcomes.
- Strong understanding of the end-to-end data and AI lifecycle, including data engineering, data management, cloud data platforms, business intelligence, advanced analytics, machine learning, generative AI, deployment, governance, and adoption.
- Experience leading proposals, RFPs, solution architecture, staffing, effort estimation, cost estimation, commercial inputs, and transition planning.
- Ability to lead multidisciplinary teams across business consulting, data engineering, analytics, AI, architecture, program management, and change enablement.
- Bachelor’s or master’s degree in engineering, computer science, data, analytics, operations, business, or a related discipline.
Industry Experience
- Preferred experience in Manufacturing Analytics, Automotive, Mobility, Industrial Manufacturing, Heavy Equipment, Industrial Products, Aerospace, Transportation, or related manufacturing-intensive sectors.
- Automotive OEM, Tier 1 supplier, connected vehicle, manufacturing engineering, plant operations, supply chain, quality, warranty, or aftersales experience is highly desirable.
- Experience working with large, complex global manufacturers or industrial enterprises with distributed plants, functions, and technology environments.
Preferred Qualifications
- Experience supporting organizations such as automotive OEMs, automotive suppliers, industrial manufacturers, equipment manufacturers, or engineering-intensive enterprises.
- Experience with Azure, AWS, GCP, Databricks, Snowflake, Microsoft Fabric, Power BI, Tableau, or comparable data and analytics ecosystems.
- Exposure to smart manufacturing, Industry 4.0, connected factory, digital thread, digital twins, predictive maintenance, industrial IoT, and manufacturing execution environments.
- Experience shaping or leading GenAI use cases in engineering, manufacturing, supply chain, quality, warranty, service, knowledge management, or commercial operations.
- Experience building an industry offering, center of excellence, reusable assets, strategic partnerships, or high-performing multidisciplinary teams.
Leadership Competencies
- Executive presence and trusted-advisor mindset
- Consultative selling and commercial orientation
- Executive storytelling, influence, and presentation capability
- Manufacturing and operational business acumen
- Strategic thinking with strong execution discipline
- Financial acumen and account-growth mindset

Apply About employer

More about this job

Responsibilities

The Senior Engagement Manager will lead strategic client relationships and drive large-scale analytics, AI, and digital transformation programs within the manufacturing and automotive sectors. They are responsible for executive storytelling, business development, and ensuring high-quality delivery across complex, multi-workstream engagements.

Requirements

Candidates must possess 12-18 years of experience in analytics, data, AI, or management consulting with at least five years of client-facing leadership. A bachelor's or master's degree in a relevant field is required, along with proven ability to manage portfolios valued up to $15M annually.

Skills

Client Leadership
Executive Engagement
Data Analytics
Artificial Intelligence
Digital Transformation
Manufacturing Operations
Supply Chain Management
Strategic Planning
Business Development
Account Growth
Program Management
Solution Architecture
Financial Acumen
Stakeholder Management
Change Enablement
Consulting

Visa sponsorship

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Keywords

Analytics
Artificial Intelligence
Digital Transformation
Manufacturing
Automotive
Supply Chain
Cloud Migration
Data Engineering
Generative AI
Machine Learning
Management Consulting
Industry 4.0
Azure
AWS
GCP
Databricks
Snowflake
Power BI
Tableau
Digital Twins
Industrial IoT
Strategic Roadmap
Executive Storytelling
Commercial Leadership
Program Governance
Business Intelligence
Predictive Analytics
Optimization
Change Management
Stakeholder Engagement

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