Snowflake Data Architect (With AI experience)

Ovii's Interpretation of the Role

We need a senior data architect to build and govern a unified AI‑ready data platform that powers conversational agents, dashboards, and LLM applications. The role owns the end‑to‑end data stack, defines data contracts, and ensures security, compliance, and high‑quality AI outputs across multiple domains.

Role Snapshot

• Senior Data Architect
• AI‑focused data platform ownership
• Enterprise‑scale lakehouse & data mesh design
• Governance, security, and compliance
• Cross‑consumer AI data services

Must-Have Requirements

• Python
• SQL
• PySpark
• Kafka
• Databricks
• Delta Lake
• Snowflake
• AWS cloud services
• Docker
• Kubernetes
• Terraform
• GitHub Actions
• LLM APIs
• Vector databases
• Knowledge graphs
• data engineering
• AI/ML data platform
• lakehouse
• data mesh
• governance
• security
• LLMOps

Nice-to-Have Signals

• MLflow
• FastAPI
• Observability tooling

Work Setup

• Location: India, India
• Work mode: REMOTE
• Remote scope: UNSPECIFIED
• Employment type: Full-Time

Not Specified in JD

• Salary range
• Visa sponsorship
• Relocation
• Notice period
• Travel
• Security clearance
• Coding test

What You'll Likely Work On

• Design and own a unified AI‑ready data platform that ingests, transforms, stores, and serves data for all AI consumers.
• Create multi‑domain lakehouse and data‑mesh models with versioned schemas, lineage, and low‑latency APIs.
• Build and maintain semantic layers, feature stores, and knowledge graphs to enable context‑aware AI reasoning.
• Implement retrieval infrastructure for RAG pipelines, including vector stores and hybrid search layers.
• Develop ML/LLMOps pipelines, model registries, experiment tracking, and production monitoring.
• Define and enforce data governance, RBAC/ABAC policies, and compliance controls for both human and AI agents.
• Establish observability, quality gates, and SLAs for AI output accuracy, data freshness, and system reliability.
• Lead architecture reviews, create reference designs, and enable data engineering teams through workshops and standards.

Good Fit If You Have

• Enjoys translating business requirements into robust data contracts and semantic models.
• Comfortable driving modernization of legacy pipelines to cloud‑native, AI‑ready architectures.
• Experienced collaborating with AI engineers, data scientists, and product owners to deliver end‑to‑end solutions.