The Data Platform Architect is responsible for defining and governing the enterprise data platform architecture that supports analytics, reporting, and AI/ML initiatives. The role ensures data platforms are scalable, secure, reliable, and cost-efficient while aligning with business and technology strategies. Working closely with Product Management, Data Engineering, Cloud, Security, and Analytics teams, the architect provides technical leadership, establishes standards and reference architectures, and drives the evolution of enterprise data capabilities.

Key Responsibilities

Job Summary The Data Platform Architect is responsible for defining and governing the enterprise data platform architecture that supports analytics, reporting, and AI/ML initiatives. The role ensures data platforms are scalable, secure, reliable, and cost-efficient while aligning with business and technology strategies. Working closely with Product Management, Data Engineering, Cloud, Security, and Analytics teams, the architect provides technical leadership, establishes standards and reference architectures, and drives the evolution of enterprise data capabilities.

Key Responsibilities Define and maintain enterprise data platform strategy, architecture standards, and design patterns. Develop target-state architectures, technical documentation, and architectural roadmaps. Evaluate and govern data platform, integration, and ETL/ELT technology selections.

Provide architectural guidance for data pipelines, analytics platforms, and integration solutions. Establish standards for scalability, reliability, observability, security, and disaster recovery. Ensure compliance with data privacy, governance,



and regulatory requirements.

Standardize data integration approaches, including batch, streaming, and event-driven architectures. Partner with engineering teams to translate architectural standards into implementable solutions. Drive cost-efficient platform design and support FinOps initiatives.

Assess emerging technologies and recommend architectural improvements, including AI-enabled data engineering capabilities.

Skill

Requirements

Data Platforms &

- Databases Snowflake Azure Data Lake (ADLS) Microsoft Fabric Databricks SQL Server PostgreSQL Oracle Data Engineering ETL/ELT architecture and orchestration (Matillion) Data modeling and governance Batch, streaming, and event-driven integrations Data lineage, observability, and reliability engineering Cloud &
- Automation Azure and Google Cloud CI/CD for data platforms Infrastructure as Code (IaC) Platform automation and operational readiness Programming &
- Analytics SQL Python Analytics-ready dataset design AI/ML data platform enablement Integration &
- Enterprise Systems API integrations (Apigee) Salesforce FACETS ServiceNow Soft Skills Technical leadership Architecture governance Stakeholder communication and presentation Problem-solving and strategic planning Agile and Waterfall delivery methodologies Other Requirements Bachelor's degree in Computer Science, Information Technology, Data Science, or related field. 7+ years of database engineering experience, including 3+ years in architecture design. Master's degree and healthcare domain experience preferred.

Experience with enterprise integrations, APIs, and up-to-date cloud-based data ecosystems.

📌 Senior Technical Architect (Mississauga)
🏢 HCLTech
📍 Mississauga