Job description

Required Qualifications • 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. • Preferred Qualifications • 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 / transit / infrastructure organizations. • Relevant cloud or data architecture certifications. • Familiarity with enterprise data governance, MLOps, and responsible-AI practices. • Additional Skills and Information: Preferred Qualifications • 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 / transit / infrastructure organizations. • Relevant cloud or data architecture certifications. • Familiarity with enterprise data governance, MLOps, and responsible-AI practices.

Requirements

Must-haves

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.

Nice-to-haves

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 / transit / infrastructure organizations.
Relevant cloud or data architecture certifications.
Familiarity with enterprise data governance, MLOps, and responsible-AI practices.
Additional Skills and Information: Preferred Qualifications
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 / transit / infrastructure organizations.
Relevant cloud or data architecture certifications.
Familiarity with enterprise data governance, MLOps, and responsible-AI practices.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

azureawsgcpaiml

Platform: jobdiva
Effort: medium