Senior Transit Engineer supporting and growing Rail Control Systems practice across Canada. Leading technical consultancy and business development efforts for transit programs including Calgary Green Line project.
About the role
- Enterprise Architect for Data and AI at Medtronic providing key architectural leadership for strategic initiatives. Shaping scalable data and AI solutions to enhance healthcare access and equity.
Responsibilities
- Serve as the Enterprise Architect for Data and AI, acting as the primary architectural authority and trusted advisor for data, analytics, AI, and GenAI initiatives across the enterprise.
- Define, guide, and influence end-to-end architectures for data and AI solutions, ensuring alignment with business strategy, enterprise standards, platform roadmaps, and long-term transformation objectives.
- Partner closely with Enterprise Architecture, Data Platforms, Advanced Analytics, SAP COE, IT Value Streams, and Business teams to shape solution designs that are scalable, secure, compliant, and future-ready.
- Provide hands-on architectural guidance across the full lifecycle of data and AI solutions, including data ingestion, transformation, feature engineering, analytics, model development, deployment, monitoring, and lifecycle management.
- Advise on AI and data platform strategy, including cloud-native data platforms, analytics services, ML platforms, GenAI services, vector databases, orchestration frameworks, and integration patterns.
- Establish and evolve reference architectures, architectural patterns, and design guardrails for Data and AI to promote reuse, reduce technical debt, and accelerate delivery.
- Ensure data governance, privacy, security, and Responsible AI principles are embedded into solution designs in partnership with Security, Privacy, and Compliance stakeholders, particularly in regulated environments.
- Review and influence architectural decisions to avoid unnecessary customization, minimize parallel or duplicative solutions, and maximize leverage of enterprise-standard platforms and native capabilities.
- Support innovation and digital transformation initiatives by identifying pragmatic applications of emerging data and AI technologies and advising where they can deliver tangible business outcomes.
- Act as a technical thought leader and mentor to architects and senior engineers across the organization, helping raise overall architectural maturity in Data and AI domains.
- Communicate complex architectural concepts clearly and effectively to a broad audience, including senior IT leadership and business stakeholders, translating technical decisions into business impact.
Requirements
- Bachelor’s degree
- 15+ years of experience with a bachelor’s degree or 13+ years of experience with an advanced degree
- Strongly Preferred: Bachelor’s or advanced degree in Computer Science, Information Technology, Engineering, or relevant discipline; advanced degree strongly preferred
- Experience with SAP data and analytics landscapes, including S/4HANA, BDC, Data Sphere, MDG, and SAP-native analytics and integration patterns.
- Hands-on exposure to GenAI architectures, including large language models, retrieval-augmented generation (RAG), prompt engineering, and AI-enabled workflows.
- Experience defining or applying Responsible AI frameworks, AI governance models, or ethical AI practices.
- Prior experience in medical technology, healthcare, or other highly regulated industries.
- Familiarity with enterprise architecture frameworks and tooling, while maintaining a pragmatic, outcome-driven mindset.
- 15+ years of IT experience with deep, hands-on expertise in data engineering, data architecture, and analytics platforms.
- 7+ years of experience designing and influencing enterprise-scale data architectures, including data warehouses, data lakes/lakehouses, and real-time or event-driven data platforms.
- Strong experience with public cloud platforms and cloud-native data services such as Snowflake, Databricks, BigQuery, Azure Synapse, or equivalent technologies.
- Demonstrated experience working with AI, machine learning, and GenAI solutions, including understanding of model lifecycle management, MLOps concepts, and enterprise AI integration patterns.
- Deep understanding of data governance, metadata management, data quality, privacy, and security, especially within highly regulated environments.
- Proven ability to influence without direct authority, working across multiple teams and stakeholders to drive alignment and high-quality architectural outcomes.
- Strong written and verbal communication skills, with the ability to translate complex technical concepts into clear, actionable guidance for both technical and non-technical audiences.
- Track record of staying current with emerging trends in data, AI, and GenAI, and applying them thoughtfully within enterprise constraints.
Benefits
- Health, Dental and vision insurance
- Health Savings Account
- Healthcare Flexible Spending Account
- Life insurance
- Long-term disability leave
- Dependent daycare spending account
- Tuition assistance/reimbursement
- Simple Steps (global well-being program)
- Incentive plans
- 401(k) plan plus employer contribution and match
- Short-term disability
- Paid time off
- Paid holidays
- Employee Stock Purchase Plan
- Employee Assistance Program
- Non-qualified Retirement Plan Supplement (subject to IRS earning minimums)
- Capital Accumulation Plan (available to Vice Presidents and above, or subject to IRS earning minimums)
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