Manager, Enterprise Data Solutions
- Vancouver, BC, Canada
The expected base salary range for this position is $135,000 – $165,000.
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Job details
- Pay
- The expected base salary range for this position is $135,000 – $165,000.
- Experience
- 3+ years of experience designing or delivering enterprise data solutions, data architecture, analytics platforms or related technologies.
- Posting language
- English
- Posted
Original job description
Interested in joining one of Canada’s top performing asset managers?
We are looking for a Manager, Enterprise Data Solutions to help build and deliver scalable data capabilities across the organization.
Working closely with the technology leadership including Senior Manager, Enterprise Data Solutions, this role will provide both technical, strategy and people leadership across our enterprise data environment. You will help translate our data strategy into practical solutions, lead important data initiatives, and develop strong partnerships across investment, operations and technology teams.
A key part of this role is also helping us build greater leadership depth and operational resilience within Enterprise Data Solutions. The successful candidate will develop broad knowledge across our data platforms, architecture and key business processes, and be capable of assuming leadership responsibility across important initiatives when required.
Our offices currently operate on a hybrid model with three days in office.
What You Will Do
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Data Strategy Execution: Work with the Senior Manager to translate the enterprise data strategy into a practical roadmap, priorities and deliverables.
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Data Architecture & Solutions: Lead the design and implementation of scalable data solutions, data models, integration patterns and platforms supporting investment and enterprise use cases.
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Delivery Leadership: Take ownership of significant data initiatives from design through implementation, coordinating engineers, analysts, business partners and technology teams.
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AI & Advanced Data Capabilities: Help integrate AI, machine learning and intelligent automation into enterprise data solutions where they provide meaningful business value.
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Data Platforms: Support the implementation and evolution of enterprise data platforms, including data lakes, analytics environments and cloud-based data services.
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Data Governance & Controls: Help establish practical standards for data quality, ownership, lineage, controls and responsible use of AI and data.
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Business Partnership: Work closely with investment management, operations and technology teams to understand business requirements and translate them into sustainable data solutions.
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Team Leadership: Lead, coach and develop data professionals while creating clear accountability, strong engineering practices and a collaborative team environment.
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Leadership Depth & Resilience: Develop working knowledge across critical Enterprise Data Solutions responsibilities, platforms and stakeholder relationships so that leadership and decision-making can continue effectively when priorities or availability change.
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Continuous Improvement: Identify opportunities to simplify the data environment, reduce manual processes, improve reliability and increase reuse across the organization.
What You Bring
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Bachelor’s or master’s degree in Computer Science, Data Science, Engineering, Information Systems or a related discipline.
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6+ years of relevant experience, ideally within Investment Management, Asset Management or Financial Services, with exposure to investment, operations, data or technology functions.
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3+ years of experience designing or delivering enterprise data solutions, data architecture, analytics platforms or related technologies.
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Experience leading technical teams, projects or significant workstreams with accountability for delivery.
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Strong understanding of modern data architecture, data modelling, integration and cloud-based data platforms such as Azure, Microsoft Fabric or AWS.
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Practical understanding of AI, machine learning and intelligent automation and how these capabilities can be incorporated into enterprise data solutions.
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Working knowledge of programming and data technologies such as Python, SQL or comparable tools.
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Strong understanding of data governance, data quality, controls and enterprise data management practices.
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Ability to work effectively with both senior business stakeholders and technical teams, translating between business needs and technology solutions.
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Strong leadership, communication, problem-solving and analytical skills.
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Experience within investment management data domains such as portfolio, security, transaction, reference, market or operational data would be an asset.
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Experience supporting large-scale data transformation or modernization programs would be an asset.
The expected base salary range for this position is $135,000 – $165,000. The midpoint represents our general market target for a fully qualified and experienced individual performing the role. Actual starting salary may fall below or above the midpoint depending on the candidate's relevant experience, skills and qualifications, as well as internal equity considerations. Further questions may be directed to the HR team during the interview process.
What We Offer
At Connor, Clark & Lunn Financial Group, we’re "invested in our greatest asset, you". Our shared goals reflect what matters most to our people:
- Your community: we foster belonging through collaboration, inclusion and flexibility. Enjoy social events, volunteering and a strong commitment to corporate social responsibility. Our flexible work practices are designed to support work-life balance and provide employees with flexibility in where and how they work
- Your growth: we prioritize your development with meaningful work, continuous learning budgets, paid study days and support for professional designations.
- Recognizing you: your contributions are rewarded with competitive total compensation, retirement savings support, wellness credits, enhanced parental leave, and comprehensive health benefits.
For a closer look at how you can build your career with us, we invite you to explore cclgroup.com.
We are committed to providing an inclusive, accessible recruitment and selection process. We welcome and encourage applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the recruitment and selection process. Please contact talentacquisition@cclgroup.com if you require accommodation.
AI may be used to support certain stages of our screening & recruitment process. These tools support, but do not replace, human judgment and decision-making.
More about this job
Responsibilities
The Manager, Enterprise Data Solutions will lead the design and implementation of scalable data architectures and integrate AI capabilities to support investment and operational goals. They are responsible for coaching data professionals and fostering strong partnerships across technology and business teams to ensure effective data governance and delivery.
Requirements
Candidates must possess a bachelor's or master's degree in a relevant field and at least 6 years of experience, including 3 years in enterprise data solutions or architecture. Strong proficiency in modern data platforms, cloud technologies, and leadership experience within financial services is required.
Skills
- Data strategy
- Data architecture
- Data modeling
- Cloud platforms
- Azure
- Microsoft Fabric
- AWS
- Python
- SQL
- Data governance
- Data quality
- AI
- Machine learning
- Intelligent automation
- Team leadership
- Project management
Benefits
- Retirement savings support
- Wellness credits
- Enhanced parental leave
- Comprehensive health benefits
- Continuous learning budgets
- Paid study days
- Flexible work practices
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Management & Leadership
- Finance & Accounting
- Software
Keywords
- Enterprise Data Solutions
- Data Strategy
- Data Architecture
- Data Modeling
- Cloud-based Data Services
- Azure
- Microsoft Fabric
- AWS
- AI
- Machine Learning
- Intelligent Automation
- Python
- SQL
- Data Governance
- Data Quality
- Investment Management
- Asset Management
- Financial Services
- Data Lakes
- Analytics Environments
- Data Integration
- Leadership
- Engineering Practices
- Operational Resilience
- Data Lineage
- Portfolio Data
- Market Data
- Modernization
- Stakeholder Management
- Technical Strategy