Data Architect-Consumer Data and AI

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.
Modern 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

Work arrangement
No