Senior Data Architect

Datavail

. Lead discovery and current-state assessments of client data estates .

Posted 10/30/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting end-to-end data solutions on Azure, including Microsoft Fabric, with a strong focus on data engineering, data warehousing, and analytics. Proficient in dimensional modeling, CI/CD practices, and leading technical teams in a client-facing environment.

Highest-signal resume keywords

End-To-End Architecture OwnershipExpert-Level Dimensional Modeling SkillsAdvanced SQL (T-SQL and Spark SQL)Microsoft Certified: Fabric Data Engineer AssociateExperience Leading Technical Teams

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Hard Skills

Data EngineeringData WarehousingAnalyticsDimensional ModelingSQL (T-SQL and Spark SQL)Python/PySparkCI/CDInfrastructure as CodeData Vault 2.0AI and Machine Learning Solutions

Soft Skills

Strong Written and Verbal CommunicationMentoring Technical TeamsClient Engagement

Tools & Technologies

Microsoft FabricAzure Synapse AnalyticsAzure SQLPower BIAzure Machine LearningData FactoryAzure BoardsJiraGit-Based WorkflowsDataOps

Certifications & Qualifications

Microsoft Certified: Fabric Data Engineer Associate (DP-700)Microsoft Certified: Azure Solutions Architect Expert (AZ-305)Microsoft Certified: DevOps Engineer Expert (AZ-400)Databricks Certified Data Engineer Professional

Industry Keywords

HealthcareFinancial ServicesManufacturingRetailPublic SectorFedRAMPGovernment Cloud

Tech Stack

Tools & technologies

AzureCloudPySparkPythonSDLCSparkSQLVault

About the role

Key responsibilities & impact

Lead discovery and current-state assessments of client data estates
Define target-state and transition architectures for analytics, data warehousing, Lakehouse, real-time and operational data workloads
Produce solution architecture documents, architecture diagrams, ADRs, non-functional requirements and capacity plans
Evaluate platform and build-versus-buy trade-offs across Fabric, Databricks, Azure Synapse Analytics and Azure SQL
Apply Azure Well-Architected Framework and Cloud Adoption Framework guidance
Plan and lead migrations to Fabric and Azure
Lead architecture and design reviews, maintain reference architectures and standards, manage exceptions and track technical debt
Architect end-to-end Microsoft Fabric solutions across OneLake, Lakehouse, Warehouse, Data Factory, Dataflows Gen2, Spark notebooks, Real-Time Intelligence and Power BI
Design OneLake strategies and govern Fabric capacities, consumption, budgets and cloud/Fabric spend
Design Power BI semantic models and integrate Fabric with the wider Azure estate
Design network, identity, governance and security controls
Own conceptual, logical and physical data models and define modeling, naming, key, partitioning and file-layout standards
Establish SDLC, DevOps, CI/CD, infrastructure-as-code, testing and DataOps practices
Define support models, SLAs/SLOs, escalation paths, training, documentation and handoff criteria
Work within Agile delivery using Azure Boards or Jira
Design data foundations and architectures supporting AI and machine learning, including Azure Machine Learning, Fabric Data Science, Azure OpenAI, RAG, Fabric IQ, Foundry IQ, knowledge graphs and agentic solutions
Define GenAIOps practices and AI cost and capacity planning
Support pre-sales through technical discovery, solution approaches, estimates, proposals and SOWs
Serve as technical lead and primary technical contact on client engagements
Review implementation, conduct readiness reviews and provide production sign-off
Present architecture and recommendations to technical and executive audiences
Identify follow-on opportunities and contribute to account growth
Develop reusable Datavail solution accelerators and intellectual property
Evaluate new Microsoft Fabric, Azure, data and AI capabilities and turn successful experiments into practice guidance
Lead technical delivery teams and mentor team members
Contribute to hiring, interviewing and onboarding for the Data & Analytics practice

Requirements

What you’ll need

Bachelor's degree in computer science, information systems, engineering or a related field, or equivalent professional experience
10+ years of experience in data engineering, data warehousing or analytics, including 5+ years in a data or solution architect role
3+ years designing and delivering data solutions on Azure, and hands-on delivery experience with Microsoft Fabric in production
End-to-end architecture ownership of at least two enterprise-scale data platform implementations
Expert-level dimensional modeling skills and working knowledge of Data Vault 2.0 and normalized modeling
Advanced SQL (T-SQL and Spark SQL) and working proficiency in Python/PySpark; working knowledge of DAX and KQL
Practical experience implementing CI/CD, Git-based workflows and infrastructure as code for data platforms
Experience in a professional services, consulting or client-facing delivery environment, including pre-sales and estimation
Experience leading and mentoring technical teams
Strong written and verbal communication, with the ability to produce clear architecture documentation and lead client workshops
Ability to travel up to 25% to client sites
Authorization to work in the United States
Preferred: Microsoft Certified: Fabric Data Engineer Associate (DP-700)
Preferred: Microsoft Certified: Azure Solutions Architect Expert (AZ-305)
Preferred: Microsoft Certified: DevOps Engineer Expert (AZ-400)
Preferred: Databricks Certified Data Engineer Professional
Preferred: Delivered AI or machine learning solutions in production, including RAG or generative AI workloads on Azure
Preferred: Experience designing ontologies or knowledge graphs, and hands-on work with Fabric IQ or Foundry IQ
Preferred: Experience implementing AI governance or responsible AI programs, and GenAIOps evaluation and monitoring for production AI solutions
Preferred: Experience with Azure Government (GCC, GCC High) or other government cloud environments, including FedRAMP and related compliance requirements
Preferred: Experience architecting multi-tenant data platforms
Preferred: Experience with transformation and data quality frameworks
Preferred: Industry experience in healthcare, financial services, manufacturing, retail or the public sector

Benefits

Comp & perks

Ability to travel up to 25% to client sites