Description

• 8+ years of overall experience in data engineering, data architecture, software engineering, or a closely related field, with 6+ years in an architecture-focused role.

• Multi-cloud experience — hands-on design and delivery across at least two major cloud providers (e.g., Azure, AWS, GCP).

• Multi-database experience across relational, NoSQL, analytical/warehouse, and vector or graph database technologies.

• Multi-AI experience — practical work across a range of AI/ML and generative-AI frameworks, models, and platforms (e.g., LLMs, ML pipelines, RAG, model orchestration).

• Strong requirements-gathering and stakeholder-facing skills: proven ability to extract clarity from ambiguity and write actionable specifications.

• Excellent written and verbal communication; able to explain complex technical concepts to non-technical audiences and secure buy-in.

• Hands-on experience delivering solutions with agentic development tooling / AI-assisted development workflows.

• Demonstrated experience taking solutions from concept through approval to production implementation.

• Primary recent experience on the Microsoft Azure stack (e.g., Azure Data services, Synapse/Fabric, Azure OpenAI, Azure ML).

• Hands-on development experience with Microsoft Copilot tooling (e.g., GitHub Copilot, Copilot Studio, M365 Copilot). Exceptional candidates without Copilot experience will be considered.

• Experience in large, complex, or public-sector Government / transit / infrastructure organizations.

• Relevant cloud or data architecture certifications.

• Familiarity with enterprise data governance, MLOps, and responsible-AI practices

Key Skills

Education

Any Gradute