Python jobs in Canada

As of November 1, 2025, Sunoco LP has successfully completed its acquisition of Parkland Corporation. For more information, please visit www.sunoc olp.com.

Competitive Benefits. Meaningful Extras. Unmatched Value.

As the Data Architecture Lead, you will guide the transformation and migration of our data ecosystem toward a modern, target-state architecture built on Azure and Databricks, while ensuring continuity and integration with existing legacy environments (primarily AWS-native data lake and SQL Server) as needed. This role demands a unique blend of technical expertise, strategic vision, and leadership to drive innovation and deliver business value through data.

• Platform Modernization & Migration: Driving the transition from legacy systems to Azure-based architecture, ensuring interoperability and minimal disruption.
• Architecture & Engineering: Designing and implementing a high-performing data platform leveraging Databricks, cloud-native services, and common data models.
• Integration & Enablement: Ensuring the platform provides seamless data access and sharing capabilities, enabling stakeholders to easily discover, consume, and utilize trusted data assets.
• AI & GenAI Enablement: Helping build platform capabilities to support advanced AI workloads and emerging technologies for data-driven decision-making.
• Data Governance & MDM: Implementing strong governance frameworks and Master Data Management to maintain data integrity and compliance.
• Agile Delivery: Applying agile methodologies and tools such as Jira and ServiceNow to enable rapid iteration and continuous improvement.

• Strategic Planning: Develop and execute a comprehensive roadmap for data platform modernization, driving migration from legacy systems (AWS-native data lake, SQL Server) to Azure and Databricks.
• Enterprise Data Architecture:
  • Data Strategy & Architecture: Define architecture principles and standards to ensure consistency across systems and platforms.
  • Develop and maintain an enterprise data architecture that aligns with organizational goals and supports the modernization roadmap.
  • Create and maintain enterprise-wide data standards, guidelines, and best practices for modeling, integration, and governance.
  • Provide strategic leadership on emerging data technologies such as knowledge graphs, real-time analytics, and generative AI data foundations.

• Data Modeling & Master Data Management:
  • Design logical and canonical data models that ensure interoperability, scalability, and alignment with enterprise architecture principles.
  • Build and maintain canonical data models to standardize data exchange across applications, integration layers, and business domains.
  • Provide leadership for enterprise Master Data Management (MDM) strategy and implementation, including domain modeling, survivorship rules, golden record creation, and stewardship processes.

• Data Governance, Quality & Compliance:
  • Collaborate with stakeholders to develop and enforce data governance policies, procedures, and standards.
  • Define and operationalize data lifecycle management processes, including creation, storage, usage, archival, and deletion.
  • Design end-to-end data and analytics solutions that meet business requirements and align with organizational goals.
  • Implement data quality frameworks covering profiling, cleansing, monitoring, and remediation.

• Data Platforms & Infrastructure:
  • Lead data modernization initiatives, including migration planning, platform selection, and hybrid/multi-cloud strategies.
  • Architect and optimize enterprise data platforms including data lakes, warehouses, and Lakehouse environments.
  • Implement metadata management strategies such as business glossaries, lineage, and cataloging to enhance data discoverability and trust.

• Data Integration & Interoperability:
  • Develop enterprise data integration strategies using APIs, event-driven architectures, ETL/ELT pipelines, and streaming platforms.
  • Collaborate with engineering teams to design APIs that enable efficient data exchange between internal systems and external platforms and promote interoperability, scalability, and ease of consumption.
  • Establish data observability practices to monitor pipeline health, data freshness, schema drift, and anomalies.

• Analytics, AI/ML & Data Products:
  • Enable governed self-service analytics ecosystems through semantic layers, curated datasets, and BI platform standards.
  • Guide data product development using product thinking to create reusable datasets, APIs, and analytical assets.

• Security, Privacy & Risk Management:
  • Collaborate with cybersecurity teams to ensure data protection, threat detection, and regulatory compliance.

• Organizational Enablement & Leadership:
  • Champion data literacy and responsible data use across business and technical teams.
  • Develop KPIs and metrics for data architecture performance to measure value, reliability, and adoption.

• Business Strategy and Operations Knowledge:
  • Understand the organization's business strategy and operations to ensure platform capabilities support business objectives.
  • Collaborate with business leaders to identify opportunities where data solutions can drive efficiency, revenue growth, or cost savings.

• Stakeholder Interaction:
  • Engage with key stakeholders, contributing to discussions with business executives, IT leadership, and external partners to understand business needs and communicate architectural concepts effectively.

• Bachelor's or Master’s degree in Computer Science, Data Science, Information Systems, Business Administration, or related field.

• Proven experience (10+ years) working with data platforms and architecture, data engineering, or analytics, including exposure to cloud technologies and modern data ecosystems.
• Strong technical proficiency in data platform architecture and data management technologies (e.g., SQL, Python, Spark, Databricks, cloud-native services), with experience in building scalable, secure, and high-performing data solutions.
• Experience with Databricks implementation and optimization is highly desirable.
• Strong understanding of data warehousing design, data modeling, and scalable architecture principles.
• Excellent communication, interpersonal, and leadership skills, with the ability to effectively collaborate and influence stakeholders at all levels of the organization.
• Strategic thinking and problem-solving abilities, with a track record of driving innovation, delivering results, and managing complex projects or initiatives.
• Solid understanding of data governance principles, regulatory requirements (e.g., GDPR, CCPA), and best practices for data privacy and security.
• Experience working in Agile or Scrum methodologies, with proficiency in project management tools (e.g., Jira).
• Business acumen and market orientation, with the ability to translate business needs into technical requirements and deliver data products that create tangible value for customers and stakeholders.
• Leadership qualities such as mentorship, coaching, and team development, fostering a culture of learning, collaboration, and continuous improvement.

Humble. Hungry. Smart. Does this sound like you?

Do others describe you as being a down-to-earth achiever? Someone who thinks outside the box and always strives to do more than what is required? Someone who sees the bigger picture? You sound brilliant to work with!

We Want You To Shine:

We are committed to providing equal opportunities to all applicants. If you require accommodation due to a disability, you will have an opportunity to notify us when scheduling your interview.

Belonging Matters. Because You Do:

We are an equal opportunity employer and encourage applications from all qualified individuals. Our ability to work as one team across Canada, the United States, and the Caribbean is foundational to our success. We show up as our authentic selves each day and create space for one another’s unique contributions.

We respect the diverse cultures, traditions, and perspectives of Indigenous Peoples and seek to achieve equitable partnerships and opportunities with Indigenous communities.

The Fine Print:

Candidates must be legally eligible to work in the country in which they applied. Regrettably, we are unable to sponsor employment visas at this time.

Final candidates will be required to undergo a confidential pre-employment background check, including but not limited to educational, criminal, credit, drug and alcohol, and/or fitness for duty testing.

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