Data Architect - Enterprise Data Platforms and AI-Ready Solutions

Data Architect

Project Role : Data Architect
Project Role Description : Define the data requirements and structure for the application. Model and design the application data structure, storage and integration.
Must have skills : Data Analytics
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education

Data Architect to design, govern, and evolve enterprise scale data platforms that support analytics, AI, and business critical decision making within complex consumer goods and retail environments. The role requires strong hands on and conceptual expertise across modern data architecture, including data modeling, integration, governance, and cloud platforms, with the ability to translate business processes and KPIs into scalable, governed data solutions. The architect is also expected to have practical exposure to Generative AI and Agentic AI architectures to ensure the data foundation is AI ready, secure, and extensible.

Key Responsibilities
Define and own end to end data architecture across conceptual, logical, and physical layers, aligned to enterprise standards and business domains.
Design and evolve modern data platforms such as lakehouse and domain oriented architectures to support analytics, BI, operational reporting, and AI workloads.
Architect scalable data models and pipelines across consumer and retail domains including product, customer, sales, inventory, supply chain, pricing, promotions, and financial analytics.
Translate business processes, decision journeys, and KPIs into robust data models, semantic layers, and consumption ready datasets.
Define architecture for data ingestion, transformation, orchestration, governance, quality, lineage, security, and privacy, supporting batch and near real time use cases with controls embedded by design.
Establish and enforce architecture standards, reference architectures, and reusable patterns, ensuring performance, scalability, resilience, and cost efficiency.
Enable data foundations for Generative AI and agent based solutions, including RAG patterns, vectorized data access, semantic retrieval, and orchestration friendly data designs.
Collaborate with AI/ML, engineering, and security teams to ensure responsible AI adoption, observability, and compliance.
Act as a trusted advisor to business and technology stakeholders, review solution designs, mentor teams, and participate in architecture governance, solution shaping, and estimations.

Required Skills
Strong experience architecting enterprise scale data platforms.
Ability to design ingestion, storage, processing, and serving layers.
Clear understanding of scalability, resiliency, and cost efficient design in distributed systems.
Advanced hands on data modeling expertise.
Experience across conceptual, logical, and physical models.
Strong command over dimensional models, fact hierarchies, and retail aligned analytical models that support business KPIs.
Proven experience designing end to end data pipelines.
Covers batch and near real time ingestion, transformation patterns, and orchestration.
Strong understanding of dependency management, reconciliation, and data lifecycle management.
Deep practical experience with data governance architecture.
Includes metadata management, lineage, data quality frameworks, and MDM.
Strong grasp of embedding access control, security, and privacy directly into data platforms.
Extensive experience delivering data architecture in CPG and/or Retail environments.
Strong domain knowledge across merchandising, supply chain, pricing, promotions, inventory, trade spend, and financial analytics.
Ability to translate business processes into robust data designs.
Strong experience with cloud based data and analytics platforms.
Hands on architectural experience on Azure, AWS, or GCP.
Exposure to platforms such as Databricks, Snowflake, BigQuery, or Redshift.
Practical experience enabling Generative AI on enterprise data.
Experience designing RAG architectures, embedding pipelines, and vectorized data access.
Strong understanding of semantic retrieval over governed datasets.
Working knowledge of agentic AI data requirements.
Familiarity with context management, memory patterns, and tool driven workflows.
Awareness of observability and control considerations.
Mandatory experience in large scale transformation programs.
Prior work in complex enterprise landscapes with global rollouts.
Proven ability to operate within multi vendor delivery environments.
Strong stakeholder management and communication skills.
Ability to influence senior engineers, architects, and business leaders.
Comfortable operating as a design authority and advisor.

Good to Have Skills
Experience designing and implementing Data Mesh or domain oriented data architectures at scale.
Hands on exposure to streaming and event driven architectures using Kafka, Event Hubs, or Kinesis.
Experience with advanced GenAI and agentic AI tooling such as LangChain, LangGraph, MCP (Model Context Protocol), vector databases, and AI orchestration frameworks.
Exposure to enterprise grade semantic layers, conversational analytics, and decision intelligence platforms.
Understanding of omnichannel retail, digital commerce, personalization, or advanced revenue growth management (RGM) solutions.


Experience & Education
10+ years of overall experience in data engineering and data architecture roles.
5+ years of experience designing and leading enterprise scale data platforms.
Strong track record delivering CPG / Retail data and analytics programs.
Demonstrated involvement in GenAI enabled enterprise initiatives.
Bachelor s or Master s degree in Computer Science, Engineering, Data Science, or a related field.
Relevant cloud or data architecture certifications are a plus.