Role Summary :

As our Senior Data & AI Architect, you'll set the technical direction for our entire data and AI portfolio. This is a leadership role where you'll decide how all the pieces fit together, from raw source systems to the analytics and AI products our clients use every day.

You'll work directly with client stakeholders to plan delivery timelines and team capacity, while owning the architecture and governance standards that keep data secure, trustworthy, and production ready. A big part of this role is guiding our solutions from early proof-of-concept (POC) maturity into hardened, enterprise-grade platforms.

Primary Responsibilities :

- Own the Big Picture: Define the end-to-end data architecture - ingestion from operational and enterprise sources, Lakehouse storage organized in medallion layers, transformation pipelines, and the semantic layer that serves analytics and AI applications.

- Architect the AI Layer: Set reference architectures for machine learning and generative AI workloads - including RAG, model hosting and orchestration, and the evaluation and monitoring that prove a model is performing.

- Plan With Clients: Partner directly with client stakeholders to set delivery milestones, allocate team capacity, and steer the data and AI roadmap.

- Lock Down Governance & Security: Own the data governance model - cataloging, lineage, role-based access control, handling of sensitive data, tenant isolation between clients, and responsible-AI guardrails.

- Lead Production Hardening: Guide the transition of solutions from early-stage proof-of-concept builds into robust production platforms - covering orchestration, CI/CD pipelines, data quality testing, observability, and cost and performance tuning.

- Set the Technical Bar: Review architectural decisions, approve significant design changes, and maintain high engineering standards across the team, including offshore delivery partners.

Required Technical Experience & Tech Stack :

- Experience: 10 - 14+ years in data engineering, analytics, or AI delivery, including 4+ years specifically in a Data or AI Architect role on enterprise cloud platforms.

- Tech Stack: Azure Cloud, Databricks, Delta Lake, Apache Spark, Python, SQL, dbt, Azure Data Factory, Unity Catalog, Microsoft Purview, Azure OpenAI, MLflow, Power BI.

- Cloud & Platform Expertise: Deep knowledge of the Azure data platform - ADLS, Data Factory, Synapse or Fabric, and Databricks on Azure.

- Core Skills: Strong hands-on background with Python, SQL, and PySpark, plus data modeling across both dimensional warehouse and lakehouse (medallion) patterns.

- AI & ML: Experience taking machine learning and generative AI solutions to production - model lifecycle management with MLflow, RAG and vector search patterns, and prompt and evaluation frameworks.

- Governance & Security: Experience with Unity Catalog and Purview for cataloging and access control, along with data masking and multi-tenant isolation.

- Integration: Familiarity with industrial and enterprise source systems - ERP (such as SAP), process historians (such as OSIsoft PI), IoT and time-series data, APIs, and streaming platforms (Event Hubs, Kafka).

- Domain (Preferred): Prior delivery experience in energy or manufacturing.