Solution Architect- Data and AI

Michelin; Pune District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Michelin is seeking a Solution Architect- Data and AI to own architectural decisions, reference blueprints, and target-state designs while balancing latency, cost, and scalability.

You will architect end-to-end data and AI solutions on the Azure Databricks Lakehouse, enforce security, and lead cross-functional delivery with a focus on TB-PB scale.

Qualifications

• Advanced Python, PySpark and SQL proficiency required.
• Expertise with Databricks, Delta Lake and Spark Structured Streaming.
• Strong Azure stack knowledge: ADLS Gen2, ADF, Synapse, Azure ML, AKS, Event Hubs, Key Vault.
• Experience designing multilevel Lakehouse architectures at TB-PB scale.
• Deep DB expertise: PostgreSQL, Synapse, Snowflake, ADLS.
• ML/DL fluency with scikit-learn, TensorFlow or PyTorch and MLflow.
• Hands-on PII/GDPR data handling and cloud security.

Responsibilities

• Own architectural decisions, ADRs, blueprints and target-state designs.
• Architect end-to-end data and AI pipelines on lakehouse platforms.
• Optimize large-scale PySpark/Databricks workloads and tuning.
• Design data models across PostgreSQL, Snowflake and Synapse.
• Productionize ML/DL models and expose endpoints for batch/real-time inference.
• Enforce security and governance (PII/GDPR, Purview, Key Vault).
• Build CI/CD and MLOps pipelines and instrument Observability.
• Coach delivery teams and collaborate with Data Science, Product, QA and Platform leads.

Skills

Advanced Python

PySpark

SQL

Databricks

Delta Lake

Spark Structured Streaming

Azure stack

ADLS Gen2

ADF

Synapse

Azure ML

AKS

Event Hubs

Key Vault

Medallion Lakehouse

PostgreSQL

Snowflake

TensorFlow

PyTorch

MLflow

PII/GDPR

CI/CD

MLOps

Terraform

Bicep

Docker

Kubernetes

Job description

Solution Architect- Data and AI

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.

Example: Decide between Postgres Db/Mongo Db, Decide between ODAP/One System Platform, etc.

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
• Strong Azure stack: ADLS Gen2, ADF, Synapse, Azure ML, AKS, Event Hubs, Key Vault
• Proven design of medallion Lakehouse architectures at TB-PB scale
• Deep DB expertise: PostgreSQL, Synapse, Snowflake, ADLS
• ML/DL fluency: scikit-learn, TensorFlow, PyTorch, MLflow
• Hands-on PII/GDPR data handling and cloud security
• CI/CD & MLOps: Azure DevOps or GitHub Actions, Terraform/Bicep, Docker, Kubernetes

Behavioural Competencies :

• Communication Clarity - Produces clear, concise architecture documents, runbooks and presentation materials appropriate to the audience.
• _Continuous Learning & Curiosity_ - Keeping up with industry advances,trends and applies relevant innovations pragmatically.
• _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

• Azure OpenAI, AI Search, RAG, vector databases
• IoT ingestion patterns
• Data Mesh / federated governance experience