Data Architect-Consumer Data and AI

Location-PAN India

We are looking for a Data Architect to anchor the technology backbone of our Data practice. You will design the customer data foundations -CDP architecture, identity resolution, and unified Customer 360 profiles, that power measurement, personalisation, and AI-driven engagement for global enterprise clients across Retail & CPG, Telecom & Media, Financial Services, Healthcare, and Automotive.

You will operate at the intersection of data architecture and customer experience: shaping client solutions in pre-sales, leading architecture workstreams on engagements, and defining how enterprise data estates must evolve to support real-time decisioning and agentic AI. You will be a senior technical voice in a fast-growing, entrepreneurial practice - with direct influence on our offerings, our talent, and our clients' outcomes.

Architecture & Delivery

- Customer 360 architecture - Design end-to-end customer data architectures: ingestion, identity resolution, unified profiles, consent and governance, and activation across marketing, service, and commerce channels.
- CDP & AEP leadership - Lead CDP solution design and implementation architecture, with Adobe Experience Platform (RT-CDP) as a primary anchor — XDM schema design, identity graphs and namespace strategy, merge policies, segmentation, and destination activation.
- Up-to-date data platform design - Define lakehouse/medallion architectures and data product patterns that make customer data AI-ready — quality, lineage, semantic consistency, and low-latency access for downstream ML and decisioning.
- AI & agentic enablement - Architect the data and context layer for next-best-action engines, real-time personalisation, and agentic AI systems — including feature/context stores, vector and retrieval (RAG) patterns, event streaming, and API/MCP-based access for AI agents.




- Governance & trust - Establish data governance, privacy-by-design (GDPR/DPDP/CCPA), consent management, and responsible-AI guardrails as first-class architecture concerns, including permissions, auditability, and human-in-the-loop checkpoints for autonomous systems.

Client & Practice Leadership

- Advisory & assessment - Lead technical discovery and architecture assessments with client stakeholders - including our Customer 360 Assessment diagnostic, translating business ambitions in CX into pragmatic architecture roadmaps.
- Pre-sales & solutioning - Shape solution architectures, estimates, and technical narratives for proposals; present credibly to CDO/CTO/CMO-level audiences and handle technical objections in the room.
- Practice building - Contribute reusable reference architectures, accelerators, and points of view to our three offerings - Customer 360, Experience Intelligence, and Hyper-Personalisation and mentor engineers and consultants across the team.

Must-Have Experience

- 8+ years in data engineering/architecture, with 4+ years as a hands-on architect on enterprise-scale programmes.
- Deep expertise in customer data: CDP platforms (Adobe Experience Platform strongly preferred; Salesforce Data Cloud, Segment, or Tealium also valued), identity resolution, and building unified customer profiles from fragmented sources.
- Strong cloud data platform experience on at least one of Azure, AWS, or GCP — including Databricks and/or Snowflake, streaming (Kafka/Event Hubs/Kinesis), and modern ELT tooling (dbt or equivalent).




- Proven data modelling depth: dimensional and Data Vault modelling, event/behavioural data models, and API/schema design (including XDM or comparable canonical models).
- Working proficiency in SQL and Python; comfort reviewing and guiding engineering teams' code and pipeline designs.
- Demonstrated experience architecting data for AI/ML use cases: feature pipelines, model-serving data flows, churn/propensity/NBA scoring, and MLOps fundamentals.

AI & Agentic AI Experience (Core to This Role) We expect genuine, hands-on exposure, not just familiarity with the vocabulary. Strong candidates will bring several of the following:

- Experience designing data and retrieval architectures for GenAI applications: embeddings, vector databases (e.g., Pinecone, pgvector, Azure AI Search), RAG pipelines, and grounding strategies over enterprise customer data.
- Exposure to agentic AI frameworks and patterns - LangGraph, CrewAI, AutoGen, Semantic Kernel, or equivalent , and to Model Context Protocol (MCP) or tool/function-calling patterns for giving agents governed access to data.
- Understanding of multi-agent orchestration, state and memory management for long-running agents, and where agents should and should not be used in CX workflows (e.g., autonomous service resolution, proactive journey interventions, closed-loop VoC triage).
- Experience with enterprise AI platforms such as Azure OpenAI, Amazon Bedrock, or Vertex AI, and with AEP-adjacent AI capabilities (Adobe AI Assistant, Customer AI/Attribution AI) is a strong plus.
- Awareness of AI evaluation, observability, and governance - evals, hallucination and drift monitoring, cost control, and frameworks such as ISO/IEC 42001 or the EU AI Act as they affect customer-facing AI.

Your Qualifications

- Min 8-12 years of experience as Data architect

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