Adobe Experience Platform (AEP) Architect

Role overview

Adobe Experience Platform (AEP) Architect at Bounteous

Responsibilities

• Design data pipelines, transformation logic, and orchestration for high-volume, multi-source profile and event data.
• Design data governance with Data Usage Labelling & Enforcement (DULE), data governance policies, consent, and privacy (GDPR, CCPA, Adobe Privacy Service).
• Design computed attributes, derived datasets, and event-based audience qualification rules.
• Design event-triggered (Journey) and audience-triggered (Campaign) experiences with decisioning and offer management (Offer Decisioning / Decision Management).
• Design derived fields, calculated metrics, and attribution models for cross-channel journey analysis.
• Drive performance and cost optimization: profile store sizing, dataset hygiene, query optimization, and licence-entitlement monitoring.

Required qualifications

• 10+ years in data, martech, or customer-data platform engineering / architecture.
• 4+ years hands-on Adobe Experience Platform across at least two of RT-CDP, AJO, and CJA.
• At least 2 full lifecycle AEP implementations delivered (discovery through activation and hypercare).
• 3+ years in a Solution Architect / Lead Architect role with client-facing pre-sales and proposal ownership.
• Demonstrated experience with enterprise-scale, multi-source, high-volume customer data programs.
• Core AEP & Data Skills
• XDM schema design, field groups, classes, identity namespaces, and union schema modelling.
• Real-Time Customer Profile, Identity Service, identity graphs, and merge policies.
• Data ingestion: Source Connectors, Streaming Ingestion API, Data Landing Zone, batch ingestion, and mapping.
• Segmentation Service (batch / streaming / edge), computed attributes, and audience activation.
• Data governance: DULE labels, policies, consent management, and Privacy Service.
• Query Service / Data Distiller, SQL, derived datasets, and accelerated query / data views.
• Strong SQL and at least one of Python / Spark for data engineering and transformation.
• Understanding of cloud data ecosystems (Snowflake, Databricks, BigQuery, S3, Azure, GCP) and ETL / ELT patterns.
• Application & Integration Skills
• Adobe Journey Optimizer: journeys, campaigns, channels, decisioning, and offer management.
• Customer Journey Analytics: connections, data views, derived fields, calculated metrics, and attribution.
• Adobe Experience Platform APIs, Adobe I/O, Destination SDK, and Source SDK for custom integrations.
• Adobe Web SDK / Edge Network, Tags (Launch), and event-forwarding / server-side collection.
• Integration patterns with AEM, Adobe Analytics, Adobe Target, Marketo, and Adobe Commerce.
• Pre-Sales & Architecture Skills
• Executive stakeholder management and C-suite / CDO communication.
• Solution scoping, effort estimation, and program-level sizing for large data engagements.
• Risk identification, mitigation planning, and architectural decision records (ADRs).
• Familiarity with Adobe partner deal-registration and co-sell motion.
• Skill / Domain
• Adobe Certified Expert (ACE) - AEP, RT-CDP, AJO, or CJA.
• Experience with AEP Edge Network, Web SDK, and server-side / event-forwarding collection.
• Exposure to AJO B2B Edition and account-based journey orchestration.
• Hands-on with Data Distiller for advanced SQL analytics, BI extracts, and ML feature engineering.
• Experience integrating AEP with AEM, Adobe Analytics, Adobe Target, and Adobe Commerce in a unified DX stack.
• Prior experience at a Global Systems Integrator (GSI), Adobe Professional Services, or Adobe Consulting Services (ACS).
• Familiarity with composable CDP debates and build-vs-buy data architecture trade-offs.
• Understanding of data residency, sovereignty, and Healthcare Shield / privacy-regulated deployments.

Employment details

• Location: India

Application details

• Apply Customer AI (propensity / churn) and Attribution AI within AEP for predictive audience and journey use cases.

About the employer

• Practice-building mandate - shape Bounteous’ AEP Centre of Excellence, accelerators, and capability roadmap for India. 1.
• Contribute to Bounteous’ AEP CoE: accelerators, reference architectures, implementation playbooks, and reusable assets.

Additional role details

• Own the full Adobe data stack - RT-CDP, AJO, CJA, and the underlying Experience Platform services, not a single point product.
• End-to-end data lifecycle authority - from source connectors and ingestion through activation, governance, and measurement.
• Pre-sales partnership with Adobe Professional Services and the India alliance team on joint pursuits and CXO conversations.
• AI-augmented practice - leverage GenAI and Customer AI / Attribution AI within a Claude Preferred Services Partner.
• Solution Architecture & Pre-Sales
• Lead architectural discovery with CXO, CDO, Marketing, and Data Engineering stakeholders to translate business goals into AEP solution blueprints.
• Visualize enterprise customer requirements into target-state data architectures spanning ingestion, profile, segmentation, journeys, and analytics.
• Own technical scoping, effort estimation, and the solution narrative in RFP / RFI responses and proposals.
• Partner with Adobe Professional Services / ACS and the partner alliance team on joint solutioning, co-sell, and go-to-market propositions.
• Present reference architectures, data flow diagrams, and ROI / value cases at the executive level.
• Define implementation roadmaps with phasing, dependencies, and risk-mitigation strategies. 2.
• Data Ingestion & Data Engineering
• Architect ingestion across batch and streaming sources: Source Connectors, Streaming Ingestion API, Data Landing Zone, HTTP API, and Adobe / cloud-native connectors (S3, Azure Blob, GCS, Snowflake, Kafka).
• Establish data quality, validation, error-handling, and monitoring frameworks (Data Hygiene, Dataset monitoring, Observability).
• Define schema-on-ingest mapping, dataset partitioning, and TTL / retention strategy aligned with platform limits and cost.
• Architect integrations with downstream data warehouses / lakehouses and reverse-ETL patterns where required. 3.
• Data Modelling, Identity & Profile
• Design XDM (Experience Data Model) schemas - classes, field groups, data types, and descriptors - for both Profile and ExperienceEvent use cases.
• Architect Identity Service strategy: identity namespaces, identity graph design, private graph, and identity stitching across known and anonymous profiles.
• Govern the Real-Time Customer Profile: union schemas, profile enrichment, merge policies, and profile / event store sizing.
• Establish a scalable schema governance model and naming conventions across multiple sandboxes and business units. 4.
• Segmentation, Audiences & Activation
• Architect audience strategy: batch, streaming, and edge segmentation; segment definitions; and Audience Composition for complex cohorts.
• Define activation patterns to destinations - advertising, social, email, and custom destinations via Destination SDK.
• Architect federated audience composition and data collaboration patterns where relevant.
• Govern audience overlap, suppression logic, and consent-aware activation. 5.
• Adobe Journey Optimizer (AJO)
• Architect orchestration of real-time and scheduled journeys across email, push, SMS, in-app, and code-based channels.
• Define data flows between RT-CDP profile, AJO journeys, and message channels, including profile lookups and external data sources.
• Govern message frequency capping, throttling, deliverability, and channel configuration.
• Architect AJO B2B Edition / journeys for account-based motions where applicable. 6.
• Customer Journey Analytics (CJA)
• Architect the CJA data view, connection, and stitching strategy across cross-channel datasets.
• Define the relationship between AEP datasets, CJA connections, and downstream reporting / Workspace projects.
• Govern data governance and access controls within CJA and integration with Adobe Analytics where co-existing. 7.
• AI / ML & Intelligent Services
• Define ML feature requirements, training data design, and the operationalisation of model scores into profiles and segments.
• Architect feature engineering and integration with Data Distiller / Query Service for advanced analytics and ML preparation. 8.
• Technical Leadership & Governance
• Lead, mentor, and review onshore / offshore AEP engineering and data teams (5-20 practitioners).
• Define platform standards: sandbox strategy, schema governance, naming conventions, CI/CD for AEP configurations, and version control.
• Participate in architecture review boards and present designs to client enterprise architecture and data-governance teams.