Salesforce Data Cloud Architect

Capgemini•Mississauga, ON

1d•CA$83,144 - CA$195,060•Hybrid

About The Position

The Data Cloud Architect is the senior technical authority for the Identity Resolution programme, responsible for designing and governing the end-to-end Salesforce Data Cloud solution. This is a client-facing role requiring deep hands-on experience with enterprise-scale Data Cloud deployments in retail or consumer-facing industries. The Architect defines the resolution strategy — spanning deterministic, probabilistic, and household-level identity matching — and ensures the overall solution is technically sound, scalable, and fit for production at large customer graph volumes.

Requirements

8+ years in data architecture, with hands-on experience in Salesforce Data Cloud/CDP
Strong knowledge of identity resolution (deterministic, probabilistic, fuzzy matching)
Experience in data modeling, unified customer profiles, and large-scale data solutions
Familiarity with data integration patterns (batch and real-time), APIs, and ETL/ELT processes
Exposure to retail or consumer-facing data environments and cloud platforms (AWS/Azure/GCP)
Proven client-facing consulting experience with strong stakeholder management
Ability to translate business requirements into technical solutions
Strong analytical, problem-solving, and decision-making skills
Experience leading cross-functional and offshore teams
Excellent communication and presentation abilities

Responsibilities

Design the end-to-end Data Cloud solution architecture — including unified profile schema, Data Model Objects (DMOs), Data Lake Objects (DLOs), and the identity resolution ruleset framework covering deterministic matching (exact email, phone, loyalty ID), fuzzy/normalised matching, and probabilistic scoring across incomplete or low-signal customer records.
Define the identity resolution strategy for a multi-source retail environment — governing how identifiers from loyalty, POS, e-commerce, and digital behavioural channels are prioritised, weighted, and reconciled into a single authoritative customer profile.
Configure and validate match rule thresholds in Data Cloud — balancing precision (avoiding false merges) against recall (maximising graph coverage), with specific attention to household-level grouping logic where shared address, device, or payment signals are used to link individual profiles.
Design the data ingestion architecture — defining batch versus near-real-time ingestion patterns, Data Service Credit optimisation strategy, and source-to-target mapping standards for all contributing data streams.
Establish technical governance standards for the offshore delivery team — architecture decision records, integration patterns, data quality thresholds, naming conventions, and configuration review sign-off before promotion to UAT or production.
Lead technical solutioning sessions with client IT, data engineering, and analytics stakeholders — translating business identity and activation requirements into Data Cloud configuration and integration specifications.
Own resolution quality benchmarking — defining match rate KPIs (deterministic rate, overall resolution rate, household linkage rate) and the methodology for measuring and reporting identity graph quality throughout the programme.
Monitor and control Data Cloud credit consumption — defining ingestion frequency, profile unification cadence, and segmentation refresh schedules to manage cost as data volumes and use case scope expand.

Benefits

Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs
Other benefits as provided by local policy and eligibility

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