Job Title: Enterprise Data Architect/Data Scientist(5926-1)
Location: 2 Broadway - MTA Headquarters, NY
Note: *HYBRID - 3 days onsite and 2 days remote
Job Description:
- The MTA is seeking an experienced Data & AI Architect to design, define, and deliver enterprise data and artificial-intelligence solutions across a large, multi-department organization.
- This is a hands-on architecture role that blends deep technical expertise with strong stakeholder engagement: the architect will partner directly with business and operational teams across the MTA to surface ambiguous, poorly defined problems, translate them into clear and actionable requirements, secure approval, and implement solutions using modern agentic development tooling.
- The ideal candidate is equally comfortable in a whiteboard session with a non-technical department head and in the details of a multi-cloud data and AI platform.
- They bring recent, primarily Azure-based experience and hands-on fluency with Copilot-style AI development tooling, along with broad exposure to multiple cloud providers, database technologies, and AI/ML frameworks.
Key Responsibilities
Engage stakeholders across any MTA department to elicit, clarify, and shape nebulous or emerging data and AI use cases into well-scoped opportunities.
Translate business needs into clear, actionable requirements documents that both technical and non-technical audiences can understand and act on.
Present and explain proposed solutions, trade-offs, and value to stakeholders and governance bodies, and drive requirements through to formal approval.
Architect end-to-end data and AI solutions spanning ingestion, storage, transformation, modeling, serving, and consumption layers.
Design and implement solutions using agentic development tooling to accelerate delivery while maintaining quality, security, and maintainability.
Define reference architectures, patterns, and standards for data and AI across multi-cloud and multi-database environments.
Ensure solutions meet enterprise requirements for security, privacy, data governance, cost efficiency, and regulatory compliance.
Collaborate with engineering, data science, platform, and product teams to move approved solutions from design into production.
Mentor and provide technical guidance to engineers and analysts, and champion good data and AI practices organization wide.
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, Google Cloud Platform).
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.
Additional Skills and Information:
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.
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