**Title:** Enterprise Data Architect
**Location:** Markham, ON (Hybrid)
**Contract**

**Key Responsibilities:**
- **Enterprise Architecture & Data Strategy:** Lead the creation and execution of data architecture strategies aligned with business goals and requirements. Collaborate with stakeholders across the organization to understand data needs and develop end-to-end solutions. Ensure scalable, secure, and sustainable data architecture while optimizing data flow and storage strategies.
- **Data Platform & Lifecycle Management:** Design, implement, and manage enterprise data platforms with a focus on modern data practices and cloud computing. Oversee the data lifecycle management processes, ensuring data quality, retention, security, and governance. Guide the adoption of the medallion architecture pattern for structured and organized data pipelines.
- **Data Product Management:** Champion the concept of Data as a Product, ensuring that data products are well-defined, maintainable, and provide value to the business. Facilitate the transformation of raw data into actionable insights and ready-to-use products for data consumers.
- **Cloud & Modern Development Practices:** Leverage cloud technologies to build scalable and high-performance data solutions. Drive best practices in modern development methodologies, including CI/CD and Agile practices, to enhance data product delivery.
- **Legacy to Modern Platform Migration:** Lead the efforts to convert legacy systems and data policies to modern data platforms while minimizing disruption to existing business processes. Oversee data migration strategies to ensure seamless transitions and the integration of legacy systems with cloud-based architectures.
- **Data Science & MLOps:** Collaborate with data science teams to support the development, deployment, and operationalization of machine learning models. Provide guidance on Data Science Machine Learning (DSML) platforms and MLOps practices to streamline model development and lifecycle management.

**Required Skills and Qualifications:**
- Proven experience in Enterprise Architecture with a focus on data platforms, data governance, and cloud technologies.
- Strong expertise in data lifecycle management, including data modeling, data retention, and data governance principles.
- Solid understanding of the Medallion Architecture pattern and its application in large-scale data systems.
- In-depth knowledge of Data as a Product concepts and ability to translate business requirements into tangible data solutions.
- Expertise in modern cloud platforms (AWS, Azure, GCP) and cloud-native development practices.
- Extensive experience with data science platforms, machine learning operations (MLOps), and facilitating the integration of data science models into production environments.
- Proficient in designing solutions that convert legacy data systems to modern data architectures.
- Strong communication and leadership skills to work effectively with cross-functional teams and business leaders.
- Experience with data integration, ETL processes, and data warehousing concepts.

**Preferred Qualifications:**
- Certification in cloud platforms (AWS Certified Solutions Architect, Azure Architect, etc.)
- Experience with modern data engineering tools and platforms such as Apache Kafka, Spark, or Databricks.
- Familiarity with data privacy and compliance frameworks such as GDPR, CCPA, and HIPAA.