Technical Architect - Data Cloud at Salesforce – India - Hyderabad | Jobyssey

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Job Category

Customer Success

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

ROLE OVERVIEW

The Data Cloud Architect — Migration Factory is a cross-track technical authority responsible for designing and governing the Salesforce Data Cloud implementation layer that underpins every migration wave within the Migration Factory. Bridging the gap between legacy data estates and the Salesforce unified customer platform, this role owns the end-to-end Data Cloud architecture — from ingestion stream design and identity resolution to unified profile modelling, segmentation activation and data readiness assessment for Agentforce. This position extends the readiness architecture into the Migration Factory delivery engine — ensuring every customer migrated across Marketing Cloud Next, Revenue Cloud, ITSM and Tableau Next tracks has a well-governed, AI-ready, unified data foundation in Salesforce Data Cloud from day one. The architect is equally responsible for the data migration discipline — owning data profiling, ETL strategy, transformation mapping, reconciliation standards and cutover data integrity across all migration tracks. As a member of the Migration Factory CoE, this role drives continuous improvement of data migration and Data Cloud accelerators, ensuring each wave delivers higher data quality and faster time-to-insight than the last.

RESPONSIBILITIES

Data Cloud Architecture — Cross-Track Ownership: Design the Salesforce Data Cloud architecture that serves as the unified data foundation for all Migration Factory tracks — owning data stream configuration, identity resolution rules, unified profile schema, data lake object (DLO/DMO) design, calculated insights and segmentation activation to downstream clouds.
Data Readiness Assessment: Lead data readiness assessments for every incoming migration wave — profiling source system data estates across Marketing Cloud, CPQ/Billing, ITSM and BI platforms to identify data quality gaps, schema mismatches, consent record completeness and AI-readiness of the data for Agentforce activation.
Agentforce Data Readiness: Design the data architecture that makes migrated customer data AI-ready for Agentforce — ensuring unified profiles, grounding data, retrieval-augmented generation (RAG) context and structured data actions are correctly configured in Data Cloud and available to Agentforce agents post-migration.
Data Migration Strategy — Factory-Wide: Own the cross-track data migration methodology for the Migration Factory — defining standards for data profiling, ETL pipeline design, transformation mapping, staging area architecture, bulk load sequencing, cutover window design, dry run execution and reconciliation sign-off across all five tracks.
ETL & Integration Pipeline Design: Architect ETL and data integration pipelines for migrating high-volume source system data into Salesforce objects and Data Cloud — selecting appropriate tools (Informatica, Talend, MuleSoft, Azure Data Factory, AWS Glue) based on source system, volume and transformation complexity.
Identity Resolution Design: Design and implement Salesforce Data Cloud identity resolution rulesets — defining match rules, reconciliation rules and individual/household profile merge strategies for migrated customer data from multiple legacy source systems.
Consent & Compliance Architecture: Architect the consent data migration strategy across all tracks — ensuring GDPR, CAN-SPAM, CASL and POPI consent records, suppression lists and data processing agreements are correctly migrated into Data Cloud and propagated to activation targets including Marketing Cloud Next.
Data Quality & Validation Framework: Design and enforce the factory-wide data quality framework — defining validation rules, anomaly detection thresholds, reconciliation counts, completeness checks and data quality warning standards in Data Cloud and Tableau Next post-migration.
Data Cloud Product Expertise & Roadmap: Maintain deep, current knowledge of Salesforce Data Cloud product capabilities, roadmap, feature releases and best practices — translating new product capabilities into updated factory playbooks and delivery standards.
Cross-Track Collaboration: Work closely with the Marketing Cloud Next, Revenue Cloud, ITSM, Tableau Next and DevOps Track Architects — ensuring Data Cloud integration points, data stream dependencies and unified profile activation are correctly wired into each track's delivery plan and cutover sequence.
Trusted Advisor to Clients: Serve as the senior data architecture advisor to client CDOs, Data Engineering leads and Enterprise Architects — articulating the vision for a unified, AI-ready data platform built on Salesforce Data Cloud as the outcome of the migration programme.
Factory Accelerator Development: Build and maintain the Data Cloud migration accelerator library — data stream templates, DLO/DMO schema blueprints, identity resolution config guides, consent migration playbooks, ETL pipeline templates, reconciliation scripts and data quality dashboards — as reusable factory assets.
Platform Development for Factory Tooling: Design and build Apex-based Data Cloud API callout frameworks, batch data validation utilities and LWC-based data reconciliation dashboards deployed on the Salesforce platform to support factory data migration operations.
Continuous Improvement — Factory Feedback: Capture Data Cloud and data migration lessons learned after every wave, feeding structured improvements back into the MDLC Phase 7 Factory Feedback loop — driving measurable reduction in data migration effort, defect rate and cutover duration wave-over-wave.

CORE TECHNICAL SKILLS — MUST HAVE

Salesforce Data Cloud — Deep Expertise: Advanced hands-on knowledge of Data Cloud — data streams, data lake objects (DLO), data model objects (DMO), identity resolution, unified profiles, calculated insights, segmentation, activation targets and Data Cloud APIs.
Agentforce Data Readiness: Understanding of how Data Cloud unified profiles, grounding data, structured data actions and retrieval-augmented generation (RAG) context feed Agentforce agents — and how to design the data architecture to make migrated data AI-ready.
Data Migration Methodology: Proven expertise in end-to-end enterprise data migration — data profiling, ETL pipeline design, transformation mapping, staging architecture, bulk load sequencing, dry run execution, reconciliation and cutover planning across high-volume source systems.
ETL & Data Integration Tools: Hands-on experience with at least two ETL/integration tools — Informatica Cloud (IDMC), Talend, MuleSoft, Azure Data Factory, AWS Glue, Fivetran or similar — for large-scale data extraction, transformation and load into Salesforce and Data Cloud.
Identity Resolution Design: Experience designing Data Cloud identity resolution rulesets — match rules, reconciliation rules, individual/household profile merge logic and deduplication strategies for multi-source customer data estates.
Consent & Compliance Data Architecture: Expert knowledge of consent data migration — GDPR, CAN-SPAM, CASL, POPI — and how to architect consent record migration, preference data flows and suppression list propagation within Data Cloud and to activation targets.
Data Architecture & Modelling: Strong understanding of relational and dimensional data modelling, star/snowflake schemas, canonical data model design, ERD development and Large Data Volume (LDV) strategies for Salesforce platform objects and Data Cloud DMOs.
Salesforce Platform & API Development: Ability to write Apex Batch classes, REST callout frameworks and LWC data validation tools for factory migration operations. Experience with Salesforce Bulk API 2.0, Composite API and Data Cloud Ingestion API for high-volume data operations.
Data Quality & Reconciliation: Expertise in designing data quality frameworks — validation rules, anomaly detection, completeness checks, reconciliation count matching and data quality warning configuration in Salesforce and Tableau Next post-migration.
Integration Architecture: Understanding of enterprise integration patterns — event-driven architecture, API-led connectivity, pub/sub messaging and CDC (change data capture) — relevant to migrating real-time data streams into Data Cloud from legacy source systems.
Platform Security & Data Governance: Knowledge of Data Cloud data governance — data spaces, field-level security, consent API, data sensitivity labels and role-based access — and how to apply compliance-aligned governance for migrated customer data estates.
Platform Development: Proficiency in Apex Triggers, Batch Apex, Schedulable classes, Governor Limit management and Apex Test Classes — combined with ability to build LWC dashboards and Salesforce Flow automations as internal factory tooling for data validation and migration progress monitoring.

PREFERRED SKILLS — GOOD TO HAVE

Hands-on experience with Salesforce Data Cloud Ingestion API, Streaming API and Calculated Insights API for real-time data activation
Knowledge of zero-copy data federation — Snowflake Data Sharing, Databricks Delta Sharing and BigQuery Omni — as Data Cloud data sources without physical data movement
Experience with dbt (data build tool) for upstream data transformation and semantic layer design feeding Data Cloud data streams
Familiarity with Customer Data Platform (CDP) migrations — migrating from Segment, Tealium, mParticle, Treasure Data or Lytics to Salesforce Data Cloud
Understanding of Salesforce Marketing Cloud Next + Data Cloud activation patterns for AI-personalised journeys post-migration
Experience with master data management (MDM) platforms — Informatica MDM, Reltio, Stibo — as source systems for identity resolution seeding in Data Cloud
Knowledge of Apache Kafka, AWS Kinesis or Azure Event Hub for streaming data ingestion into Data Cloud via Ingestion API
Familiarity with data mesh architecture principles and how federated data ownership models affect Data Cloud data stream design
Experience with Salesforce Tableau Next as a Data Cloud visualisation and data quality monitoring layer post-migration

EXPERIENCE REQUIREMENTS

8–14 years of experience in data architecture, data engineering and Salesforce platform solutions
5+ years of hands-on Salesforce Data Cloud (or legacy Salesforce CDP) implementation experience
4+ years of enterprise data migration experience — end-to-end ownership of data profiling, ETL, transformation and cutover for large-scale programmes (10M+ records)
Demonstrated experience delivering Data Cloud implementations that serve as the unified customer data foundation for multi-cloud Salesforce programmes
Proven experience working within a programme delivery model — collaborating with multiple track architects, data engineers and client data teams concurrently
Experience with Agentforce data readiness — configuring Data Cloud to support Agentforce agent grounding, structured data actions and retrieval-augmented generation

SALESFORCE & PLATFORM CERTIFICATIONS

Salesforce Data Cloud Consultant (Required)
Salesforce Certified Data Architect (Required)
Salesforce Application Architect (Required)
Agentforce Specialist (Required)
Salesforce Marketing Cloud Consultant (Preferred)
Salesforce Integration Architect (Preferred)
Informatica IDMC Certified (Preferred)
Snowflake SnowPro Core (Preferred)

CROSS-CUTTING QUALIFICATIONS

Data Migration Authority: Recognised expert in enterprise data migration — able to set and enforce data profiling, ETL, transformation and reconciliation standards across multiple concurrent migration tracks within the factory.
Agentforce / AI-Ready Data Design: Deep understanding of how Data Cloud unified profiles, grounding data and structured data actions enable Agentforce — able to design data architectures that make every migrated customer AI-ready from day one.
Cross-Track Collaboration: Comfortable working alongside Marketing Cloud Next, Revenue Cloud, ITSM and Tableau Next Track Architects — providing Data Cloud integration guidance without owning their track delivery.
Continuous Learning & Product Readiness: Demonstrated habit of hands-on product experimentation, beta participation and roadmap engagement — aligned to the Salesforce Readiness Architect mandate to stay ahead of Data Cloud and Agentforce product evolution.
Communication: Ability to translate complex data architecture decisions for both technical data engineering teams and non-technical executive stakeholders (CDOs, CIOs, Chief Data Stewards).
Factory Mindset: Committed to industrialised, repeatable delivery — building and contributing reusable accelerators, templates and playbooks that make each successive wave faster and higher quality than the last.

Unleash Your Potential

When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.

Accommodations

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