Fullstack Data Architect

Class Valuation, LLC
Denver, CO, United States
14 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

.NET Framework Application Programming Interfaces (APIs) Artificial Intelligence Data Analysis Applications Architecture Component-Based Software Engineering Application Layers Computing Platforms Microsoft Azure Cloud Computing Computer Programming Continuous Integration
+40 more
Data Architecture Information Engineering Data Infrastructure Data Integration Data Retention Query Languages Distributed Systems Middleware Fault Tolerance Monitoring of Systems Python (Programming Language) Log Analysis Node.Js Role-Based Access Control Kusto Query Language Standard Sql Responsive Web Design SQL Databases Data Streaming Web Applications Web Application Frameworks Data Storage Technologies Data Ingestion Azure Data Factory GitHub Copilot ReactJS Snowflake Apache Spark Indexer Backend Microsoft Fabric Data Lineage Apache Kafka Machine Learning Operations Front End Software Development Cloud Migration Terraform Stream Processing Databricks Microservices

Job description

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

  1. 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

  2. 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

  3. 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

  4. 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

Requirements

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), * 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)

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