Solution Architect- Data and AI

michelinhr; Pune District; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

MichelinHR is seeking a Solution Architect- Data and AI to own end-to-end data and AI architectures, delivering Lakehouse patterns on ADLS Gen2, Delta Lake, and streaming pipelines. You will optimize large PySpark workloads, design cross-platform data models, and productionize ML/DL solutions with Azure ML and AKS.

Responsibilities include enforcing security, building CI/CD/MLOps pipelines, and guiding delivery teams to align with data policy and governance.

Qualifications

• Advanced Python, PySpark, SQL proficiency.
• Expert in Databricks and Delta Lake for TB-PB scale.

Responsibilities

• 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 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, Snowflake, Synapse, and ADLS; include normalization/denormalization patterns.
• 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, Unity Catalog / Purview, GDPR.
• Build CI/CD and MLOps pipelines (Azure DevOps, GitHub Actions, Terraform/Bicep; instrument observability).
• Data Modeling Architecture/Design as part of Data and AI solutions; includes STAR schema patterns.
• Know platform components fit for requirements; choose between Postgres, Mongo, etc.
• Implement Continuous Architecture with BI and AI domain knowledge.
• Coach teams and align with Data Science, Product, QA, and Platform leads.

Skills

Python

PySpark

SQL

Databricks

Delta Lake

Spark Structured Streaming

ADLS Gen2

ADF

Synapse

Azure ML

AKS

Event Hubs

Key Vault

PostgreSQL

Snowflake

TensorFlow

PyTorch

MLflow

PII GDPR

CI/CD

MLOps

Docker

Kubernetes

Tools

Databricks

Delta Lake

Spark Structured Streaming

Azure DevOps

GitHub Actions

Terraform/Bicep

Docker

Kubernetes

Job description

Solution Architect- Data and AI - - - - - - - - - - -

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.
• 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.

• 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

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