Data Solutions Architect

Summary

As a Solutions Architect – Data Services you will define and drive end-to-end data solutions across the Data Services portfolio, translating business objectives into scalable, governed, production-ready architectures. This is a builder–architect role focused on Azure Databricks, data mesh architectures, domain-oriented data products, and Unity Catalog–based governance. This role requires a strong foundation in software architecture, data engineering, and cloud platforms, along with a deep understanding of architectural best practices, security, and compliance. This role operates at the initiative / solution level, translating business objectives into scalable, governed, and production-ready data architectures. The role requires expert knowledge of Azure Databricks, including data mesh architectures, data products, and Unity Catalog–based governance. Advance knowledge of system design is required and will be demonstrated through hands-on execution, proof-of-concepts (POCs), and cross-system solution design. You will collaborate closely with Product Management, System Architects, Engineering teams, and enterprise stakeholders to ensure solutions are both architecturally sound and practically deliverable. This is a builder–architect role: you are expected to validate architectural decisions through POCs, guide implementation across teams, and ensure designs survive real-world delivery constraints.

Responsibilities

Solution & Data Architecture- Define solution-level architectures with a strong focus on: Azure Databricks (workspaces, compute patterns, orchestration) Data mesh architectures and domain-oriented data products Unity Catalog for governance, security, lineage, and multi-workspace Contribute to the architectural vision and implementation strategy for data initiatives, ensuring alignment with business goals and platform standards. Develop high-level architectures and guide their evolution into implementable designs, collaborating with System Architects and delivery teams. Identify, document, and manage cross-system dependencies, integration points, and architectural risks. Data Platform Design & Governance- Data ingestion, transformation, and serving in Databricks Data product contracts, ownership, and lifecycle management Security and access control using Unity Catalog, Entra ID, and cloud-native controls Ensure solutions align with enterprise governance, compliance, and security standards, partnering with Enterprise Architecture and platform teams. Contribute to the evolution of reference architectures, architectural runway, and reusable data patterns across Data Services. Hands-on Execution & Proof-of-Concepts- Design and execute proof-of-concepts (POCs) to validate architectural decisions, reduce delivery risk, and explore new capabilities. Remain hands-on where appropriate, including: Python for data engineering, notebooks, and platform automation C# and Python for service integration, APIs, and platform-facing components Support teams during implementation by clarifying architectural intent, reviewing designs, and unblocking complex technical challenges. Collaboration & Delivery Alignment- Partner with Product Management and Business Owners to shape epics and features during envisioning and PI Planning. Collaborate with System Architects to ensure consistency between solution-level architecture and system-level designs. Guide Agile teams through architectural decisions during planning, execution, and promotion to production. Participate in architecture reviews, Inspect & Adapt (I&A) workshops, and ongoing solution refinement. Mentorship & Technical Leadership- Provide architectural mentorship to System Architects, Tech Leads, and senior engineers. Promote best practices in data architecture, data engineering, and platform design. Share knowledge through design reviews, technical workshops, and documentatio Architectural Design & Documentation- Develop C4 architecture models, leveraging diagram-as-code tools such as Structurizr for C4 models and PlantUML or Mermaid for sequence diagrams. Contribute to High-Level Designs (HLDs) and translate them into Low-Level Designs (LLDs), including class diagrams, sequence diagrams, and data flow diagrams. Identify and own architectural enabler features from ideation through design and delivery. Define and document functional and non-functional requirements according to the final design. Requirements 7+ years of professional experience in software and/or data engineering roles with demonstrated progression into solution-level technical leadership. 4+ years of experience designing and delivering data platforms on Azure Databricks. Hands-on knowledge of data mesh concepts and domain-oriented data products. Hands-on knowledge of Unity Catalog for security, governance, lineage, and multi-workspace patterns. Solid software engineering foundation using C# and Python for service integration, APIs, and platform automation. Experience designing solutions that span data platforms, APIs, cloud infrastructure, and downstream consumers. Proven ability to define solution-level architectures and guide them through delivery, including identifying dependencies and risks. Experience producing and consuming architectural artifacts (architecture diagrams, design narratives, C4 models, sequence diagrams). Strong understanding of cloud-native architectures, DevOps, operational considerations, and security/compliance alignment. Excellent communication skills and ability to translate complex technical concepts for diverse audiences. Bias toward execution with experience validating designs through POCs and hands-on delivery. Prior experience as a System Architect or Senior Technical Lead. Demonstrated progression into solution-level technical leadership. \n \n Selection process Meeting Aye from Resilient Co. team. Client inicial interview Kforce practice ClientTech Interview Client Mgr Interview Apply To This Job