Solution Architect – Data & AI

Position Overview Our client is seeking an experienced and hands-on Solution Architect – Data & AI with strong expertise in Azure Data Platforms to lead the architecture, design and delivery of advanced Data and AI solutions for enterprise clients across industries. This role combines technical leadership, strategic consulting and solution design to help customers derive measurable business value from their data investments. As a trusted advisor, you will partner with business stakeholders, technical teams and executive leadership to design and deliver enterprise Data & AI solutions on Azure, leveraging Microsoft Fabric, Azure Databricks, Azure Data Factory, Azure Data Lake Storage (ADLS), and Microsoft Purview, while ensuring security, governance, compliance, scalability and operational excellence. Key Responsibilities Solution Architecture & Design • Design end-to-end enterprise Data & AI architectures covering data ingestion, transformation, storage, analytics, AI and machine learning. • Architect cloud-native data platforms on Microsoft Azure using Microsoft Fabric, Azure Databricks, Azure Data Factory, Azure Data Lake Storage (ADLS), Microsoft Purview. • Build scalable, cloud-native ecosystems using Azure, Snowflake and open-source frameworks (Spark, Airflow, Kafka) • Develop AI/ML platforms incorporating MLOps, monitoring, responsible AI principles. • Define enterprise architecture blueprints, data models, integration patterns and governance frameworks aligned with business and compliance requirements. • Design and provision enterprise Azure Data Platforms with a focus on scalability, performance and resilience. • Establish enterprise data security, privacy, governance and compliance frameworks. • Design logging, monitoring, observability and alerting solutions to ensure platform reliability and operational excellence. Technical Leadership • Lead architecture reviews, technical workshops and design governance. • Provide technical leadership and mentorship to Data Engineering, Analytics and AI teams. • Drive data engineering practices (CI/CD, IaC, DevOps). • Evaluate and recommend emerging technologies for enterprise solutions. Client Consulting & Stakeholder Engagement • Translate business requirements into scalable data-driven solutions. • Advise on data strategy, architecture roadmaps and AI adoption frameworks. • Support pre-sales activities, solution demonstrations, RFP responses and executive-level presentations. • Build strong relationships with business and technology stakeholders. Delivery & Governance • Ensure architectural integrity, scalability, and compliance with data privacy standards. • Design enterprise data governance solutions leveraging Microsoft Purview • Define best practices, reusable assets and mentoring frameworks for internal teams. Qualifications & Experience • Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Technology, Artificial Intelligence or a related technical discipline. • Minimum 8 years of total experience, with at least 2 years in Data/AI solution architecture roles. • Proven experience designing and delivering enterprise-scale Azure Data Platform and AI transformation initiatives. • Proven experience designing and delivering enterprise-scale Azure Data Platform solutions using Azure Data Lake Storage, Azure Data Factory, Azure Databricks and Microsoft Fabric. • Experience designing data lakehouse architectures, optimizing large-scale analytics solutions and leveraging modern data engineering technologies such as Snowpark, dbt, Airflow and Terraform. • Expertise in CI/CD with Azure DevOps, GitHub Actions, Terraform, Docker and Kubernetes. • Strong understanding of Python, SQL and Scala and experience with API/microservice-based data integration. • Proven client-facing and advisory consulting experience with strong analytical, communication, presentation and stakeholder management skills. • Experience designing AI/ML solutions across the lifecycle, including data preparation, model deployment, monitoring, governance and MLOps practices. • Experience with Generative AI architectures, including Large Language Models (LLMs), Azure OpenAI, AI agents, Retrieval-Augmented Generation (RAG), vector databases, and AI governance frameworks. • Familiarity with AI and data engineering technologies such as Spark, Delta Lake, Kafka, Airflow, dbt etc. • Preferred certifications include: • Microsoft Certified: Azure Solutions Architect Expert • Microsoft Certified: Azure Data Engineer Associate • SnowPro Core Certification • Snowflake Advanced Architect Certification • TOGAF Certification (optional) Show more Show less

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Technology, Artificial Intelligence or a related technical discipline. Minimum 8 years of total experience, with at least 2 years in Data/AI solution architecture roles. Proven experience designing and delivering enterprise-scale Azure Data Platform and AI transformation initiatives. Proven experience designing and delivering enterprise-scale Azure Data Platform solutions using Azure Data Lake Storage, Azure Data Factory, Azure Databricks and Microsoft Fabric. Experience designing data lakehouse architectures, optimizing large-scale analytics solutions and leveraging modern data engineering technologies such as Snowpark, dbt, Airflow and Terraform. Expertise in CI/CD with Azure DevOps, GitHub Actions, Terraform, Docker and Kubernetes. Strong understanding of Python, SQL and Scala and experience with API/microservice-based data integration. Proven client-facing and advisory consulting experience with strong analytical, communication, presentation and stakeholder management skills. Experience designing AI/ML solutions across the lifecycle, including data preparation, model deployment, monitoring, governance and MLOps practices. Experience with Generative AI architectures, including Large Language Models (LLMs), Azure OpenAI, AI agents, Retrieval-Augmented Generation (RAG), vector databases, and AI governance frameworks. Familiarity with AI and data engineering technologies such as Spark, Delta Lake, Kafka, Airflow, dbt etc. Preferred certifications include: Microsoft Certified: Azure Solutions Architect Expert; Microsoft Certified: Azure Data Engineer Associate; SnowPro Core Certification; Snowflake Advanced Architect Certification; TOGAF Certification (optional).

Design end-to-end enterprise Data & AI architectures covering data ingestion, transformation, storage, analytics, AI and machine learning. Architect cloud-native data platforms on Microsoft Azure using Microsoft Fabric, Azure Databricks, Azure Data Factory, Azure Data Lake Storage (ADLS), Microsoft Purview. Build scalable, cloud-native ecosystems using Azure, Snowflake and open-source frameworks (Spark, Airflow, Kafka). Develop AI/ML platforms incorporating MLOps, monitoring, responsible AI principles. Define enterprise architecture blueprints, data models, integration patterns and governance frameworks aligned with business and compliance requirements. Design and provision enterprise Azure Data Platforms with a focus on scalability, performance and resilience. Establish enterprise data security, privacy, governance and compliance frameworks. Design logging, monitoring, observability and alerting solutions to ensure platform reliability and operational excellence. Lead architecture reviews, technical workshops and design governance. Provide technical leadership and mentorship to Data Engineering, Analytics and AI teams. Drive data engineering practices (CI/CD, IaC, DevOps). Evaluate and recommend emerging technologies for enterprise solutions. Translate business requirements into scalable data-driven solutions. Advise on data strategy, architecture roadmaps and AI adoption frameworks. Support pre-sales activities, solution demonstrations, RFP responses and executive-level presentations. Build strong relationships with business and technology stakeholders. Ensure architectural integrity, scalability, and compliance with data privacy standards. Design enterprise data governance solutions leveraging Microsoft Purview. Define best practices, reusable assets and mentoring frameworks for internal teams.