Data Architect

Data Architect
Location: Hybrid, Austin, TX
12 months with chances of extension
Visa: Role Summary
The Enterprise Data Architect will lead the design of a Data Lakehouse architecture modernizing a data environment to become the single-source of truth for a multi-sourcing service provider landscape. This role requires deep expertise in Data Architecture and Modeling, Microsoft Azure, Databricks, Unity Catalog, and semantic modeling built and operating in an Agile Software Engineering methodology using Product Oriented Delivery (POD). The architect must also be able to articulate high-level technology benefits in business terms to drive stakeholder alignment and facilitate adoption of modern data management techniques. The Data Architect partners closely with technology office, platform teams, providers, and stakeholders to translate business requirements and technology considerations into architectural designs that will lead the development of performing, governed, and production-ready data solutions expanding the platform using Agile Software Engineering methodologies (e.g. GitHub and SDLC based on CI/CD). This role owns data architecture, semantic modeling standards, and governance patterns, while enabling engineering teams to implement at scale. Key Responsibilities Architect and govern the data management platform for data ingestion, data consumption, semantic modeling, analytics, and AI readiness.
Design master data and canonical data modeling for the ability to represent the single-source-of truth for data consumers.
Design reference architecture, patterns, standards, and lower-level technical solutions documentation for the data system, ingestion, transformation, and reporting pipelines.
Integrate ServiceNow SLA data and ApptioOne financial models into the Lakehouse.
Define and enforce governance policies using Unity Catalog.
Collaborate with the client, Capgemini resources, and providers to align architecture with business goals.
Design Data Quality and exception frameworks for data engineer reusability.
Build reusable frameworks for data engineers to develop near real-time data and batch products such as customer consumption and cost for upstream consumption, detailed analysis and executive dashboards.
Champion the integration and use of data management with providers and stakeholders.
Provide architectural direction for CI/CD pipeline development and DevOps automation for data workflows.
Explain high-level technology benefits of data management to leadership and stakeholders.
Recommend and implement the most efficient operational practices for Databricks in standard build configuration. Required Skills & Experience
8+ years in Data Architecture, with 3+ years in Databricks and Power BI.
Proven experience designing and implementing Platinum or Semantic Layers.
Strong understanding of Medallion Architecture and Unity Catalog.
Hands-on integration experience with ServiceNow (SLA, CMDB, incident data).
Hands-on integration experience with ApptioOne (cost modeling, allocations).
Strong working knowledge of Python, Spark, SQL, and Power BI sufficient to define architectural patterns, review implementations, and guide engineering teams.
Experience with MLflow, Feature Store, and AI/ML pipelines.
Experience with Azure data platform services (e.g., ADLS Gen2, Azure-native orchestration, and integration patterns)
Familiarity with Azure DevOps and GitHub Actions.
Excellent communication and stakeholder engagement skills.