Solution Architect- Data and AI

Michelin; Pune District; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Michelin seeks a Data & AI Solution Architect to design and deliver end-to-end data and AI platforms. You will own architectural decisions, build medallion Lakehouse architectures, and productionize ML pipelines at scale.

You will optimize large Databricks workloads, ensure data models meet Kimball/Data Vault standards, and enforce security/compliance across the stack. Strong collaboration with BI/AI teams is essential.

Qualifications

• Advanced Python, PySpark and SQL proficiency required.
• Expertise with Databricks, Delta Lake and Spark Structured Streaming.
• Experience designing medallion Lakehouse architectures at TB-PB scale.
• Hands-off PII/GDPR data handling and cloud security.
• CI/CD & MLOps using Azure DevOps or GitHub Actions, Terraform/Bicep, Docker, Kubernetes.

Responsibilities

• Own architectural decisions and ADRs; arbitrate trade-offs on latency, cost and scalability.
• Architect end-to-end data and AI solutions including Lakehouse on ADLS Gen2 + Delta Lake.
• Optimize large-scale PySpark/Databricks workloads with partitioning, AQE, skew handling and tuning.
• Design data models across PostgreSQL and Snowflake using Kimball and Data Vault 2.0.
• Productionize ML/DL models with Azure ML, AKS and FastAPI endpoints.
• Enforce security and compliance (PII, GDPR) using Entra ID and Key Vault.
• Build CI/CD and MLOps pipelines and instrument observability.
• Lead data/AI solution architecture; cover STAR schema and normalization patterns.
• Evaluate platform components to fit requirements; implement continuous architecture.
• Collaborate across BI/AI domains and coach delivery teams; align with policy.
• Hands-on ingestion, cleansing, validation, and repository design when needed.

Skills

Advanced Python

PySpark

SQL

Databricks

Delta Lake

Spark Structured Streaming

Medallion Lakehouse

PII & GDPR Security

Azure DevOps

GitHub Actions

Terraform

Bicep

Docker

Kubernetes

Tools

Azure Data Lake Storage Gen2

Delta Lake

FastAPI

Azure ML

AKS

Job description

Own architectural decisions (ADRs), reference blueprints, and target-state designs; arbitrate trade-offs on latency, cost, and scalability.

Architect end-to-end data and AI solutions: medallion Lakehouse (Bronze/Silver/Gold) on ADLS Gen2 + Delta Lake, streaming ingestion, ML deployment pipelines.

Optimize large-scale PySpark/Databricks workloads — partitioning, AQE, skew handling, Photon, cluster tuning.

Design data models across PostgreSQL, nowflake (Kimball, Data Vault 2.0, denormalized serving).

Productionize ML/DL models via Azure ML, AKS, Functions; expose FastAPI endpoints for batch and real-time inference.

Enforce security and compliance — Entra ID, Key Vault, PII, Unity Catalog / Purview, GDPR.

Build CI/CD and MLOps pipelines (Azure DevOps, Terraform/Bicep, MLflow); instrument observability.

Data Modeling Architecture/Design must also be done by Data and AI Solution Architect

This typically includes STAR SCHEMA Design, Normalization/Denormalization Data Patterns, etc.

Ability to evaluate and recommend which platform component would be best fit for given requirement.

Implementation of Continuous Architecture

Know how about BI domain + AI domains (NLP, GEN A, RAG, Forecasting, Computer Vision, Agentic AI, LLM) average or above average knowledge of concepts and internal technicalities.

Coach delivery teams, align with Data Science, Product, QA, and Platform leads, and contribute to the CDO's data policy.

Operate hands-on when needed — ingestion, cleansing, validation, repository design, root-cause analysis.

Must-Have

Advanced Python, PySpark, SQL

Expert in Databricks, Delta Lake, Spark Structured Streaming

Proven design of medallion Lakehouse architectures at TB-PB scale

Hands-off PII/GDPR data handling and cloud security

CI/CD & MLOps: Azure DevOps or GitHub Actions, Terraform/Bicep, Docker, Kubernetes

Communication Clarity

Produces clear, concise architecture documents, runbooks and presentation materials appropriate to the audience.

Keeping up with industry advances,trends and applies relevant innovations pragmatically.

Risk Awareness & Security Mindset

Recognizing operational, security, privacy and model-risk exposures and designs to mitigate them.

Problem-Solving & Complexity Management

Decomposes ambiguous, large-scale problems into manageable components and pragmatic solutions.

Cross-Functional Collaboration & Team Enablement

Works effectively across disciplines and empowers teams to deliver.

Stakeholder Management & Influence

Builds trust with business leaders, product owners, legal, security and engineering; influences decisions without direct authority.

Strategic Thinking & Business Acumen

Understands business drivers and shapes AI solutions that deliver measurable value and align with long-term strategy.

Experience

10–15 years in data architecture, data engineering/data science.

Demonstrated delivery of at least one enterprise Lakehouse and one production AI/ML solution.

Nice-to-Have

Data Mesh / federated governance experience