Senior Director, Unified Data Platform

Why you’ll love working here :

high-performance, people-focused culture

our commitment that equity, diversity, and inclusion are fundamental to our work environment and business success, which helps employees feel valued and empowered to be their authentic selves

membership in HOOPP’s world class defined benefit pension plan, which can serve as an important part of your retirement security

competitive, 100% company-paid extended health and dental benefits for permanent employees, including coverage supporting our team's diversity and mental health gender affirmation, fertility and drug treatment, psychological support benefits of $2,500 per year, and newly extended maternity / parental leave top of 26 weeks)

optional post-retirement health and dental benefits subsidized at 50%

yoga classes, meditation workshops, nutritional consultations, and wellness seminars

access to an annual wellness reimbursement program for health and wellness-related expenses for permanent and temporary employees

the opportunity to make a difference and help take care of those who care for us, by providing a financially secure retirement for Ontario healthcare workers

Job Summary

Reporting to the VP, Enterprise Architecture and Data Governance, the Senior Director, Unified Data platform is responsible for development, implementation, and management of unified data platform. This role involves strategic planning, technical expertise, and leadership skills to ensure the unified data platform meets business needs and supports data-driven decision making. Working in partnership with both the business and technology teams, the Sr. Director, Unified Data Platform, is accountable for developing effective long-term strategies that align technology capability to support business goals.

What you will do : Strategic Planning :

Develop and implement a comprehensive data platform strategy aligned with organization’s goals.

Vision and Roadmap : Establish a clear vision and strategic roadmap for the Unified Data Platform (UDP) that aligns with the organization’s broader goals. Define key milestones, success metrics, and timelines.

Stakeholder Alignment : Collaborate with senior leadership and key stakeholders to gather input, align on business needs, and secure buy-in for the data platform strategy. This includes continuous engagement and communication to ensure alignment.

Resource Planning : Identify the necessary resources, including budget, personnel, and technology, required for the successful implementation of the data platform strategy. Develop a comprehensive resource allocation plan and secure necessary approvals and budget in alignment with our internal process.

Policy and Governance : Establish robust data governance policies and best practices to ensure data integrity, security, and compliance. Define clear data ownership, access controls, and data stewardship responsibilities.

Communication and Change Management : Develop and execute a communication plan to keep stakeholders informed and engaged. Implement change management strategies to ensure smooth adoption and transition.

Identify and evaluate emerging technologies to enhance the data platform’s capabilities.

Up to date Technology trends : Continuously monitor and assess emerging technologies in data management, analytics, and related fields. Participate in industry forums, conferences, and networking events to stay updated.

Vendor Relationships : In partnership with the PMO &G team. establish and maintain relationships with technology vendors and industry experts. Evaluate vendor offerings through pilots, proof-of-concepts, and benchmarking exercises to identify the best solutions.

Innovation Pipeline : Create an innovation pipeline to systematically assess, prioritize, and integrate new technologies. Conduct feasibility studies, cost-benefit analyses, and risk assessments for potential technologies.

Scalability and Flexibility : Ensure the data platform is designed to be scalable and flexible, capable of adapting to evolving business needs and technological advancements. Incorporate cloud-native solutions, modular architectures, and microservices where appropriate.

Continuous Improvement : Implement a continuous improvement framework to regularly review and enhance the data platform’s capabilities. Gather feedback from users, monitor performance metrics, and make iterative improvements based on user needs and technological advancements.

Platform Development :

Lead the Architecture, Design, Development, Maintenance, and Operations of the Enterprise Data Platform :

Architecture and Design : Oversee the architectural design of the data platform, ensuring it meets the organization’s needs for scalability, security, and performance. Utilize best practices in data architecture to create a robust and flexible platform.

Development : Lead the development of the data platform, including coding, testing, and deployment. Ensure the use of modern development practices and tools to enhance efficiency and quality.

Maintenance and Operations : Establish processes for the ongoing maintenance and operations of the data platform. Ensure high availability, reliability, and performance through proactive monitoring and management.

User Self-Service : Develop and maintain an end-user self-service compute platform to empower users to access and analyze data independently. Ensure the platform is user-friendly and provides necessary tools for data analysis.

Collaborate with Cross-Functional Teams to Integrate Data from Various Sources :

Data Integration : Work closely with different business units and technology teams to integrate data from various sources into the UDP. Ensure seamless data flow and integration across systems.

Cross-Functional Collaboration : Foster strong collaboration across teams to understand data requirements, resolve issues, and ensure the platform meets business needs. Conduct regular meetings and workshops to align on goals and progress.

Ensure the Platform Supports Real-Time Data Processing and Analytics :

Real-Time Processing : Implement technologies and architectures that support real-time data processing. Ensure the platform can handle large volumes of data with low latency.

Advanced Analytics : Enable advanced analytics capabilities by integrating tools and technologies that support machine learning, predictive analytics, and other advanced analytical techniques.

Leadership :

Build and Manage a High-Performing Data Team :

Team Building : Recruit, hire, and retain top talent in data management, engineering, and analytics. Ensure the team has the necessary skills and expertise to achieve the platform’s goals.

Performance Management : Set clear performance expectations, provide regular feedback, and conduct performance reviews. Implement professional development plans to foster growth and improvement.

Mentorship and Development : Provide mentorship and support to team members, helping them develop their skills and advance their careers. Encourage continuous learning and professional development.

Relationship Building Across Business and Technology Teams :

Collaboration : Establish strong working relationships with business and technology teams. Foster a collaborative environment where teams work together to achieve common goals.

Communication : Maintain open and transparent communication channels with all stakeholders. Regularly update them on progress, challenges, and successes.

Stakeholder Engagement : Engage with key stakeholders to understand their needs and ensure the data platform meets their requirements. Facilitate regular feedback sessions and incorporate stakeholder input into the platform’s development.

Foster a Culture of Continuous Improvement and Innovation Within the Team :

Innovation : Encourage the team to explore new ideas, technologies, and approaches. Create an environment where experimentation and innovation are valued and supported.

Continuous Improvement : Implement processes and practices that promote continuous improvement in all aspects of the data platform. Regularly review performance, identify areas for improvement, and implement changes to enhance efficiency and effectiveness.

What you bring :

Experience : Minimum of 15 years in data management, with significant experience in leading end-to-end data platform projects.

This new role is being created to oversee the UDP. This role will encompass design, development, testing, and operation of the platform, expanding the responsibilities of similar current roles. The ideal candidate will have extensive experience and be capable of managing end-to-end processes.

Leadership & Strategy : Lead the establishment and implementation of the UDP in alignment with the company’s IT strategy and AI initiatives.

Platform Development : Oversee the end-to-end process of designing, developing, testing, and operating the UDP.

Data Integration : Standardize data intake from various internal and external sources, ensuring consistent data quality and accessibility.

Stakeholder Collaboration : Work closely with business and technology stakeholders to understand their data needs and ensure the UDP meets those needs.

Vendor Management : Manage relationships with external data vendors, ensuring effective integration and data quality.

Team Management : Build and lead a team of data professionals, including data scientists and software engineers, to support the UDP.

Quality Assurance : Implement robust data quality, integrity, and lineage checks to ensure the reliability of the data.

Reporting & Analytics : Facilitate advanced analytics and reporting capabilities by providing trusted and high-quality data.

Technical Expertise : Strong background in data architecture, development, and operations, with hands-on experience in data quality and integrity checks.

Leadership Skills : Proven ability to lead cross-functional teams and manage complex projects.

Collaboration : Excellent stakeholder management skills, with the ability to work effectively with both business and technology teams.

Vendor Relations : Experience in managing relationships with external data vendors and integrating third-party data.

Education : Bachelor's degree in Computer Science, Information Technology, or a related field. Advanced degree preferred.

Support and Recruitment : The role will be supported by existing staff and external vendors. Recruitment will focus on finding a senior candidate, possibly from a consulting background. The process includes a detailed evaluation and multiple interview stages.