Role Description We are seeking a Salesforce Marketing Cloud Architect with deep expertise in Salesforce Marketing Cloud (SFMC) and working knowledge of Salesforce Data Cloud to lead enterprise-scale customer engagement, data activation, and personalization initiatives. This role will drive architecture strategy, solution design, integration frameworks, and governance across marketing, CRM, and digital ecosystems. The ideal candidate combines strong technical architecture skills with business acumen, stakeholder leadership, and hands-on implementation experience. This is a high-impact position at the forefront of Salesforce’s "Data + AI + CRM" strategy. You will move beyond standard marketing automation and step into the world of real-time data orchestration and AI-driven insights. This role can be fully remote/virtual/work from home. How you'll make an impact - Architectural Design: Lead the end-to-end technical architecture for SFMC (Email, Mobile, Automation Studio, Journey Builder) and Data Cloud (Ingestion, Modeling, Identity Resolution, and Calculated Insights). - Data Strategy & Integration: Define data models and ETL processes. Design complex integrations between Data Cloud, SFMC, Sales/Service Cloud, and external data lakes (e.g., Snowflake, AWS S3). - Advanced Personalization: Architect solutions using Marketing Cloud Personalization (formerly Interaction Studio) and Data Cloud Actuations to drive real-time, cross-channel experiences. - Performance Optimization and Troubleshooting: Monitor and optimize the performance of Marketing Cloud, Data Cloud, and DevOps pipelines, including data processing, campaign execution, and system efficiency. Troubleshoot and resolve technical issues related to configurations, integrations, and data flows. - Identity Resolution: Configure and optimize Identity Resolution rules within Data Cloud to ensure accurate customer stitching across disparate data sources. - Governance & Security: Establish best practices for business unit structure, data privacy (GDPR/CCPA compliance), and security protocols within the Salesforce environment. - Technical Leadership: Act as a subject matter expert (SME) for stakeholders, translating business requirements into technical specifications and guiding a team of developers/consultants. Qualifications - Bachelor’s degree in computer science, Data Science, or a related field. - 8+ years of experience in the Salesforce ecosystem, with at least 4+ years in an Architect role. - Proven track record of delivering at least one full-scale Data Cloud implementation. - Strong background in data architecture, relational databases, Strong SQL (joins, aggregations, performance tuning) and big data concepts. - Salesforce Marketing Cloud: Expert-level knowledge of AMPscript, SSJS, SQL, and the SFMC API suite. - Salesforce Data Cloud: Hands-on experience with Data Streams, Data Mapping (DMO), Identity Resolution, and creating Calculated/Streaming Insights. - Integration Patterns: Deep understanding of MC Connect, API-based integrations (REST/SOAP), and middleware solutions. - Web Technologies: Proficiency in HTML/CSS and JavaScript for cloud pages and advanced email rendering. - Excellent communication skills, with the ability to explain "the why" behind technical decisions to non-technical executives. Requirements - The ideal candidate will hold a combination of the following: - Salesforce Certified Marketing Cloud Architect - Salesforce Certified Data Cloud Consultant - Salesforce Certified Marketing Cloud Consultant - Salesforce Certified Marketing Cloud Developer Benefits - Flexible medical & dental coverage to meet your household's needs - Life, Dependent Life and AD & D Insurance options - Retirement savings including RRSP including a company match, TFSA, pension and more - Employee Stock Purchase Plan - Educational expense reimbursement - Employee assistance programs - Discounted gym membership (GoodLife Fitness) - Opportunity for flexible work arrangements - Paid sick days & personal days - Employee education recognition program - Employee referral bonus program

• Design, develop, and maintain scalable backend applications using Python. • Build, maintain, and optimize RESTful APIs and backend services. • Collaborate on frontend development using React when needed. • Design and implement cloud-native solutions leveraging AWS services. • Write clean, maintainable, reusable, and well-tested code. • Optimize application performance, scalability, reliability, and security. • Troubleshoot and resolve production issues. • Participate in software architecture discussions and technical decision-making. • Collaborate closely with Product Managers, UX/UI Designers, QA Engineers, and Software Engineers throughout the Software Development Life Cycle (SDLC). • Participate in Agile ceremonies, sprint planning, backlog refinement, technical design sessions, and code reviews. • Research, evaluate, and implement modern frameworks, tools, and engineering best practices. • Contribute to the continuous improvement of engineering standards, platform quality, and development processes.

• A cloud observability engineer’s day is about making complex systems understandable, improving signal quality, and enabling faster, smarter debugging across teams. • Check system health, review alerts/incidents. • Triage alerts • Investigate issues • Improve observability instrumentation • Build and improve dashboards • Alert optimization • Work with development teams and other engineering partners. • Continuous improvements. • Release support. • Design and implement observability frameworks using metrics, logs, and distributed tracing • Develop dashboards, alerts, and visualizations to monitor system health • Standardize observability practices across engineering teams (logging, telemetry, tracing) • Implement and manage native monitoring tools. • Build alerting systems (avoid alert fatigue) • Participate in on-call rotations • Build intelligent alerting using Improve System Reliability/ proactively reduce risk • Identify reliability risks to help harden systems against failure • Reduction in alert noise / false positives • Increased observability coverage (% of services instrumented) • Improved SLO compliance • Embed observability into applications • Add tracing/metrics into code • Standardize logging formats • Ensure all services are observable end-to-end

• Lead development of data solutions, pipelines, and API-driven database components • Drive high‑volume data processing and enterprise data architecture efforts