About the Role: We are seeking a hands-on Data Engineer to own both the underlying CRM data foundation and the Data360 platform.

The role will design, build, govern, and support scalable data models, integrations, pipelines, Data360 capabilities, and data operations for analytics, segmentation, activation, and AI use cases.

Role mandate: Optimize the CRM data foundation, pipelines, and stand up, operate, govern, and evolve Salesforce Data360 as the enterprise customer data platform, increase AI and analytics capabilities across Salesforce user communities.

Key Responsibilities: Data Architecture, Integration & Engineering Design and modernize Salesforce data models, relationships, standards, lifecycle rules, and platform data flows.

Build and maintain integrations across Salesforce, relational databases, flat files, APIs, middleware, and Informatica pipelines.

Own transformation logic, large-volume data loads, reconciliation, performance tuning, deduplication, monitoring, and error handling.

Assess data quality and technical debt and lead practical improvements to legacy data structures and integrations.

Data360, Customer Data Platform & AI Design and implement Data360 solutions that unify CRM, transaction, portfolio, behavioural, and enterprise data into trusted customer profiles.

Own Data360’s architecture, configuration, administration, ingestion, identity resolution, harmonization, segmentation, activation, monitoring, optimization, and ongoing evolution.

Translate reporting, engagement, analytics, and AI requirements into reusable Customer Data and AI capabilities.

Enable Platform AI: Salesforce AI, Tableau Next, and implement other AI-powered use cases as the platform in collaboration with the extended CRM team.

Data Governance & Documentation Establish standards for data quality, ownership, stewardship, security, access, lineage, retention, and auditability.

Maintain clear, auditable documentation of data models, flows, integration logic, controls, architecture decisions, and operating procedures.





What you Bring: Core Experience 6+ years of hands-on Salesforce experience (Sales Cloud and Service Cloud focus) Strong, hands-on data architecture and engineering experience across schema design, entity relationships, normalization, APIs, middleware, and large data volumes.

Hands-on experience defining master data management strategies, and establishing data governance rules within the Salesforce ecosystem Experience with Informatica is preferred; comparable hands on ETL experience with the ability to ramp up quickly is acceptable.

Proven ability to ingest multi-source data, build real-time ETL pipelines, map relationships in the data graph, execute identity resolution rules, and generate unified customer profiles Demonstrated experience with Platform administration, relational data modeling, security, and configuration.

Platform development experience with Flow Builder, Apex, Lightning Web Components, release management, and Dev

Ops tooling such as Azure Dev

Ops.

Programming proficiency in SQL, Java

Script, Python, Java, or a similar language. AI experimentation and a keen ability to learn and apply new AI technologies quickly.

Data360 & Emerging AI Technology Strong understanding of identity resolution, profile unification, customer data platforms, segmentation, and activation.

Exposure to Salesforce Data360/Data Cloud or a comparable customer data platform is preferred.

Deep hands-on Data360 experience is not required where the candidate has robust data architecture, modeling, integration, and data engineering capability.

Demonstrated ability to learn and apply emerging Salesforce capabilities; AI, MCP, Plugins,



Skills, APIs, Tableau

Next or other agentic experiences.

Working Style Comfortable-owning end-to-end execution and delivery independently, while collaborating with technical, business, analytics, and enterprise data teams; Individual contributor role, no direct reports.

Solid documentation discipline and ability to explain architecture decisions and trade-offs clearly.

Strong Assets Current Salesforce certifications such as Platform Administrator, Data 360 Consultant, Data Architect, Integration Architect, Agentforce Specialist, Platform Developer I/II Experience in financial services or another regulated industry with strict privacy, security, governance, and audit requirements.

Expected Outcomes A scalable, governed, and well-documented Salesforce data foundation.

Modernized data models and integrations that improve quality, trust, performance, and operational efficiency.

Data360 implemented, operated, and continuously optimized as the enterprise Customer data platform.

Trusted customer profiles and reusable data assets that enable analytics, segmentation, activation, automation, Tableau

Next and CRM AI capabilities.

Increased productivity and efficiency across business teams through expanded data, automation and AI capabilities within the Salesforce ecosystem.

Compensation: The anticipated compensation range for this role is $100,000 – $122,500 annually, which represents base salary and, where applicable, variable compensation components (e.g., annual bonus, commissions, etc.).

Actual compensation will be determined based on many factors such as role location, candidate experience / qualifications, market conditions, and internal equity. AGF aims to offer a comprehensive and competitive total rewards package designed to support the success and well-being of our employees, which may include a combination of base salary, variable compensation, benefits, and retirement savings plans. #LI-JF1 #LI-HYBRID

📌 Salesforce AI & Data Cloud Solutions Engineer (Toronto)
🏢 AGF Investments
📍 Toronto