Senior Data Architect
Job in
Boulder, Boulder County, Colorado, 80301, USA
Listed on 2026-11-02
Listing for:
Datavail
Full Time
position Listed on 2026-11-02
Job specializations:
-
IT/Tech
Data Engineering, Azure, Cloud Computing: Infrastructure & Operations
Job Description & How to Apply Below
THE ROLE
- Datavail is hiring a Senior Data Architect to lead the design and delivery of modern data platforms for our clients
- You will own the architecture of client engagements from discovery through production, with a primary focus on Microsoft Fabric and the Azure data ecosystem
- You will define target-state architectures, build the data models that underpin them, and establish the SDLC and Dev Ops practices that let client teams operate and extend what we deliver
- This is a client-facing role
- You will work directly with business stakeholders, client IT and security teams, and Datavail delivery teams of data engineers, analytics engineers and BI developers, often across several engagements at once
- Architecture and solution design
- Lead discovery and current-state assessments of client data estates, including sources, integrations, platforms, data quality, security posture and operating model
- Define target-state and transition architectures for analytics, data warehousing, Lakehouse, real-time and operational data workloads
- Produce architecture deliverables: solution architecture documents, logical and physical architecture diagrams, architecture decision records (ADRs), non-functional requirements and capacity plans
- Evaluate platform and build-versus-buy trade-offs across Fabric, Databricks, Azure Synapse Analytics and Azure SQL, and present recommendations with cost, risk and effort clearly stated
- Apply the Azure Well-Architected Framework (reliability, security, cost optimization, operational excellence, performance efficiency) and the Cloud Adoption Framework's cloud-scale analytics guidance to every design
- Design for scale and multi-domain ownership, including data mesh and hub-and-spoke patterns where they fit the client's organization
- Plan and lead migrations from on-premises SQL Server, SSIS, SSAS and legacy data warehouses, and from Azure Synapse dedicated SQL pools, to Fabric and Azure
- Lead architecture and design reviews, maintain reference architectures and standards, manage exceptions, and track technical debt
Microsoft Fabric and Azure platform - Architect end-to-end Fabric solutions across One Lake, Lakehouse, Warehouse, Data Factory pipelines, Dataflows Gen2, Spark notebooks, Real-Time Intelligence (Event stream, Eventhouse, KQL) and Power BI
- Design One Lake strategy: workspace and domain structure, shortcuts to ADLS Gen2 and external storage, database mirroring, and medallion (bronze/silver/gold) layering on Delta Lake
- Size and govern Fabric capacities (F SKUs), including workload isolation, capacity monitoring, throttling behavior and cost management
- Forecast consumption, set budgets and tagging/showback standards, monitor unit economics, and optimize cloud/Fabric spend
- Design Power BI semantic models for performance and scale, including Direct Lake, Import and Direct Query storage modes, composite models, incremental refresh, and row-level and object-level security
- Integrate Fabric with the wider Azure estate: ADLS Gen2, Azure Data Factory, Databricks and Unity Catalog, Azure SQL Database and Managed Instance, Cosmos DB, Event Hubs, Azure Functions and Azure Machine Learning
- Design network and identity controls:
Microsoft Entra , managed identities and service principals, Azure Key Vault, private endpoints and Private Link, managed virtual networks and workspace-level access - Data modeling
- Own conceptual, logical and physical data models for client solutions, from business glossary through to deployed schemas
- Apply the right modeling approach for each layer:
Kimball dimensional modeling (star schemas, conformed dimensions, bus matrix, slowly changing dimensions Types 1, 2 and
6), Data Vault 2.0 (hubs, links, satellites) for integration layers, and normalized 3NF models for operational and master data - Design canonical and enterprise data models, master and reference data structures, and entity resolution approaches
- Define naming standards, data type conventions, key strategies (surrogate, natural, hash), and partitioning and file layout for Delta tables
- Maintain models in a modeling tool (erwin Data Modeler, ER/Studio, SqlDBM or equivalent) and keep them in version control alongside code
- SDLC and Dev Ops
- Establish the delivery lifecycle for data workloads: environment strategy (dev, test, prod), branching and pull request standards, code review, release management and rollback
- Implement Fabric Git integration with Azure Dev Ops or Git Hub, Fabric deployment pipelines, and automated deployment using the Fabric…
Position Requirements
10+ Years
work experience
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