Azure Solution Architect - Data & AI

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Azure Solution Architect – Data & AI based in the United States. We are seeking a senior technical leader to design and deliver modern data and artificial intelligence solutions using Microsoft Azure, Microsoft Fabric, and Databricks. In this role, you will translate complex business requirements into scalable, secure, and governed data architectures that drive measurable business outcomes. You will lead client engagements from discovery and solution design through implementation and production deployment, while supporting presales activities and strategic solution development. Working closely with clients, data engineers, and consultants, you will provide technical direction, mentor delivery teams, and maintain high standards of quality and customer satisfaction. You will also help shape cloud delivery practices, engineering standards, and innovative data platform solutions. This is a fully remote, US-based opportunity for an experienced architect who combines deep technical expertise with strong consulting, leadership, and communication skills.

Lead solution architecture and delivery: Drive discovery, architecture, design, development, and production deployment of data and AI solutions built on Microsoft Azure, Microsoft Fabric, and Databricks. Translate business needs into technical solutions: Partner with client stakeholders to understand business objectives and develop scalable, reliable, and governed architectures aligned with organizational goals. Drive technical presales: Lead solution design, technical scoping, proposal development, statements of work, and client presentations to support business development and successful project initiation. Define data platform standards: Establish architecture patterns, engineering practices, CI/CD standards, and governance frameworks that promote consistency, scalability, security, and maintainability. Design modern data architectures: Develop data platform solutions using lakehouse architectures, medallion models, Data Vault, dimensional modeling, and modern data engineering approaches. Lead and mentor technical teams: Guide data engineers and consultants by assigning responsibilities, reviewing deliverables, providing technical feedback, and supporting professional development. Ensure delivery excellence: Manage project milestones, budgets, risks, quality, and customer satisfaction while ensuring solutions meet agreed technical and business requirements. Optimize platform performance and costs: Apply production governance, performance optimization, automation, and cost management practices to ensure efficient and reliable data platforms. Maintain client alignment: Communicate project progress, technical decisions, risks, and recommendations clearly to business and technical stakeholders throughout each engagement. Improve cloud consulting capabilities: Contribute to the continuous development of cloud offerings, delivery methodologies, and technical practices to strengthen the quality and effectiveness of client solutions. Requirements Professional experience: At least 8 years of experience designing, architecting, and delivering Microsoft data and analytics solutions, including end-to-end implementations using Azure, Microsoft Fabric, or Databricks. Data engineering expertise: Strong proficiency in PySpark, SQL, Python, ETL/ELT processes, and software or data engineering principles. Modern data architecture: Hands-on experience with scalable lakehouse architectures, medallion models, and Data Vault or dimensional data modeling. Microsoft Azure technologies: Knowledge of Azure Data Factory, Azure SQL, Azure Storage, Azure Data Lake Storage, and related cloud data services. DevOps and automation: Experience implementing CI/CD pipelines and automation using Azure DevOps and GitHub, along with knowledge of production governance, performance tuning, and cost optimization. Technical leadership: Demonstrated ability to lead project teams, assign and review technical work, maintain delivery standards, and mentor engineers and consultants. Consulting and presales: Experience supporting technical sales, solution scoping, proposal development, statements of work, and client-facing presentations. Stakeholder communication: Excellent written and verbal English communication skills, with the ability to explain complex technical concepts, align stakeholders, and communicate risks and recommendations effectively. Preferred certifications: Microsoft Cloud certifications in Fabric, Azure Data Engineering, or Azure Architecture. Preferred education: Bachelor’s degree in a related field. Additional preferred experience: Experience delivering production AI/ML solutions or leading enterprise data modernization initiatives. Location and availability: Must be based in the United States and available to work with teams and clients across US time zones. Benefits Annual on-target earnings: $180,000–$230,000, including base salary and performance-based bonus, with an 80/20 base-to-bonus ratio. Medical coverage: Medical, dental, and vision insurance. Retirement savings: 401(k) plan with a company match. Professional development: Annual training reimbursement, continuous learning opportunities, mentorship, and career development support. Paid time off: Paid vacation time and paid holidays. Remote flexibility: Fully remote work arrangement within the United States. Collaborative culture: A people-focused environment where employees can share ideas, contribute to meaningful projects, and have their work recognized. Career growth: Opportunities to expand technical expertise and advance professionally across a global technology and consulting organization. Established industry partnerships: Exposure to modern cloud technologies and enterprise data solutions through a consulting environment with extensive Microsoft ecosystem experience. Employee well-being: Additional perks designed to support employees’ well-being and long-term professional success.