Solution Architect

Position Title- Solution Architect - AI and Data

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.

What You Bring

Must-Have

• Advanced Python, PySpark, SQL
• Expert in Databricks, Delta Lake, Spark Structured Streaming
• Strong Azure stack: ADLS Gen2, ADF, Azure ML, AKS, Event Hubs, Key Vault
• Proven design of medallion Lakehouse architectures at TBPB 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

Nice-to-Have

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

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.