Data Architect with full Stack

Full Stack Data Architect Location- Denver, CO- hybrid Role Overview We are seeking an experienced Full Stack Data Architect to own end-to-end solutioning for enterprise-scale data and application modernization initiatives, with a primary focus on data architecture. This role goes beyond backend/data design — the architect is accountable for the complete technical solution, from data platform and ingestion architecture through to the application and presentation layer, ensuring all pieces fit together as one coherent system. Architect will act as the single point of technical accountability across data engineering, integration, and application layers — defining strategy, making build-vs-buy and platform decisions, and guiding engineering teams (data, backend, and front-end) toward a unified, scalable architecture. Key Responsibilities 1. End-to-End Solution Architecture Own end-to-end solutioning across data, integration, and application layers — not just the data platform in isolation Design enterprise-grade architectures spanning: Event/data ingestion and streaming pipelines Data storage, modeling, and serving layers Application and presentation layers (web apps, dashboards, APIs) Make and document key architecture decisions (platform choice, build-vs-buy, service boundaries) and ensure traceability from business requirement to technical design 2. Data Architecture (Primary Focus) Design data models and storage strategy for both real-time (streaming) and batch data Architect using Microsoft Fabric Real-Time Intelligence (Eventhouse/KQL), Lakehouse, and Fabric SQL DB, or equivalent modern data platforms Define data retention, partitioning, indexing, and data quality/lineage strategy Establish patterns for event ingestion, stream processing, and real-time serving 3. Full Stack & Application Architecture Architect the application/API layer that consumes and exposes the data platform (e.g., React front-ends, .NET/API middleware) Define integration patterns between data platform, middleware, and UI layers Guide decisions on component reuse, responsive design, and multi-experience delivery (dashboards, custom apps, embedded analytics) Ensure the application layer meets operational requirements (write-back, workflow, role-based access) alongside analytical requirements 4. Performance, Scalability & Governance Optimize ingestion throughput and query/API latency across the full stack Design for horizontal scalability, fault tolerance, and recovery Define governance standards: security (RBAC), data lineage, monitoring, and compliance 5. Solution Leadership & Delivery Ownership Serve as the accountable technical owner for the overall solution across all delivery stages — discovery through hypercare Translate business use cases into a coherent, end-to-end technical design Conduct design reviews, enforce standards, and resolve cross-layer technical trade-offs (data vs. app vs. integration) Partner closely with the Technical Project Manager on scope, sequencing, and risk Required Skills Core Expertise Proven experience architecting full stack solutions end-to-end (data + application layers), not solely a data or solely a front-end specialist Strong data architecture background: modern data platforms, streaming/event-driven design, data modeling Application architecture experience: APIs/middleware, modern web front-ends (React or equivalent) Data Engineering & Streaming Microsoft Fabric (Real-Time Intelligence, Lakehouse) or equivalent modern data platform (Databricks, Snowflake) KQL or equivalent query language — expert level Experience with Azure Event Hubs/Kafka and real-time ingestion pipelines Application & Integration React (or similar modern front-end framework) and API/middleware design (.NET, Node, or similar) Experience integrating data platforms with operational applications (dashboards, write-back workflows, role-based UIs) Cloud & Architecture Azure Data Platform expertise Microservices & distributed systems CI/CD for data and application platforms; Infrastructure as Code (Terraform preferred) Programming & Tools Strong SQL/KQL Python/Spark (good to have) Monitoring tools (Azure Monitor, Log Analytics) Preferred Qualifications Microsoft certifications: Azure Data Engineer / Fabric Analytics Engineer / Azure Solutions Architect Prior experience owning end-to-end solution architecture on a legacy-to-cloud modernization program Experience with AI-assisted development tooling (GitHub Copilot, Claude Code) for accelerated migration Knowledge of AI/ML integration with streaming data Experience Required 12+ years overall experience in data/analytics and application architecture 5+ years architecting full stack or end-to-end solutions (data platform + application layer combined)