Data Architect- Salesforce/Informatica

Horizontal Digital is an experience-forward consultancy. So, what does this mean? We help organizations not only meet ever-increasing customer expectations but set the bar higher in the process. And we deliver on this promise by putting customers at the absolute center of everything we do, helping them build stronger possibilities with our clients in the process. Our solutions are driven by strategy, creativity and execution - powered by MuleSoft, Salesforce and other enterprise platforms. Get a deeper look at our expertise by visiting the Work section of our website.
But enough about us. Let’s talk about you.
As a Salesforce Data Architect at Horizontal Digital, you will lead data strategy, architecture, governance and migration for clients’ Salesforce and connected data platforms. The Data Architect plays a critical role for the team and will lead data migration strategy and implementation on Salesforce projects. Hands-on Informatica expertise is a mandatory requirement for this role.
What you’ll do:
Work with functional and business clients to determine solutions that drive additional business value and lead data strategy, design robust data models, and optimize data infrastructure to support the company's needs.
Work with Salesforce products: Informatica, Mulesoft, Sales, Service and Marketing Cloud
Make Data Strategy decisions related to the Salesforce environment
Work creatively and analytically with clients to understand business needs and create technical solutions in a problem-solving environment
Develop solutions for scalability, while ensuring that they conform to long-term strategic priorities
Evolve and shape the strategy, architecture, platform and standards for the integration team
Create the strategy around the Data capture and migration to enable enterprises host clean, valuable data in their instances.
Be involved in pre-sales activities
Define the enterprise data strategy and target-state data architecture across operational, analytical and AI use cases, spanning Salesforce, ERP, data warehouse and lakehouse platforms
Architect Salesforce Data 360 solutions, including data streams, data model objects, identity resolution, calculated insights, segmentation and activation, and zero-copy integration with platforms such as Snowflake, Databricks, Google BigQuery and Amazon Redshift
Design master data management and Customer 360 solutions, covering golden-record strategy, match and merge, survivorship rules and reference data management
Build conceptual, logical and physical data models, including Salesforce data models designed for large data volumes (data skew, selective queries, indexing, archiving and Big Objects) and their sharing and security implications
Establish data governance operating models, including data ownership and stewardship, metadata management, data catalogues, lineage, data classification and retention policies
Set up data quality frameworks covering profiling, quality rules, scorecards, monitoring and remediation workflows
Own the data migration strategy end to end: choose the approach (big-bang, phased by wave or region, or trickle with a coexistence period), sequence loads by object dependency, and select tooling such as Informatica IDMC, MuleSoft, Talend or Azure Data Factory based on volume, complexity, reuse and licensing
Design the migration architecture on Informatica IDMC or comparable ETL tools, with a staging layer, reusable parameterised mappings, orchestrated taskflows, external ID and cross-reference strategies, and pre-load cleansing and deduplication using Informatica Cloud Data Quality
Optimise and safeguard data loads through Bulk API 2.0 tuning, avoidance of record locking and controlled bypass of automation, handling complex data such as files, history, owner mapping and multi-currency, while keeping sensitive data masked and staging access restricted
Lead migration execution and sign-off through mock loads and dress rehearsals, automated reconciliation (record counts, checksums and field-level checks), cutover with freeze windows, delta loads and rollback plans, and hypercare, including legacy CRM migrations and Salesforce org consolidations
Shape analytics and reporting architecture across CRM Analytics, Tableau and downstream data warehouse feeds
Define data archiving, backup and recovery strategies for Salesforce and connected platforms
Prepare AI-ready data foundations for Agentforce and Einstein, including grounding data, unstructured data ingestion, vector search in Data 360 and the data quality needed for trustworthy AI outcomes
Lead a data community of practice, mentoring data engineers and consultants and driving reuse of standards, models and accelerators across projects
Modern ways of working with GenAI:
Use GenAI assistants (e.g. Informatica CLAIRE, Agentforce, Claude, GitHub Copilot) to speed up data profiling, source-to-target mapping, transformation logic and SQL/SOQL authoring, with architect-level review of the output
Apply GenAI in discovery to analyse legacy schemas, data dictionaries and sample extracts, producing field-level mappings, data inventories and migration plans faster
Use GenAI to draft and maintain data architecture artefacts such as ERDs (e.g. Mermaid), data dictionaries, data standards and governance policies
Bring AI into data quality through anomaly detection, suggested quality rules, duplicate and match recommendations, and generation of synthetic or masked test data
Use AI-assisted reconciliation and validation reporting during migrations to spot gaps and data issues earlier
Define and role-model responsible AI and data practices: approved tools only, no client or personal data in unapproved tools, use of the Einstein Trust Layer where relevant, human review of AI output and clear lineage for data feeding AI models
Who you are:
Experience designing and implementing a project’s technical & data architecture
Could work closely with clients to define and derive the solutions
Ability to guide the Development team
Good understanding of Salesforce Deployment/Physical architecture
Experience working with different file standards
Experienced with Object Oriented Architecture and RESTful Architecture
A pragmatic, business-outcome-focused architect who treats data as a product and can explain data trade-offs to executives and technical teams alike
Comfortable leading data decisions across Salesforce and non-Salesforce platforms rather than limiting the design to a single tool
An early adopter of AI-assisted data engineering who brings the team along, balancing speed with accuracy, privacy and governance
What you bring:
Mandatory – Informatica: Strong hands-on experience with Informatica Intelligent Data Management Cloud (IDMC), including Cloud Data Integration (mappings, mapping tasks, taskflows, Secure Agent, pushdown optimisation), Cloud Data Quality and the Salesforce connectors, with working knowledge of Informatica MDM, Cloud Data Governance and Catalog, Cloud Application Integration and PowerCenter-to-IDMC modernisation
Experience defining the structure of the system, its interfaces and the principles that guide the client
Strong skills in system documentation (ERD’s, process flows, etc)
10+ years of client-facing consulting/professional services experience.
7+ years of experience designing, refining and implementing data migration using Informatica and other equivalent platforms
Experience working within cross-functional project team to understand requirements and deliver solutions
Evaluate and recommend data management technologies, tools, and platforms to support the organization's data strategy.
Expertise in planning and executing enterprise data migration projects, including data mapping, data cleansing, and data transformation using native Salesforce tools and third-party ETL tools (specifically Informatica and MuleSoft, including DataWeave), minimizing downtime, blackout and data loss during migration processes. Informatica is a must have.
Proven track record leading large-volume Salesforce migrations end to end using Informatica or comparable ETL tools (e.g. Talend, Jitterbit, SSIS, Azure Data Factory), including legacy CRM migrations and org consolidations, backed by strong SQL for staging, profiling and reconciliation
Prior experience in migrating and integrating data from various sources, including external systems, databases, and files while ensuring data quality during the process.
Oversee data integration processes between systems, enabling seamless data flow across applications and platforms.
Experience in designing and developing complex data models, including custom objects, fields,

Work arrangement
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