Azure Solution Architect - Data & AI

Accountabilities: 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.