Solution Architect – Data & AI

Our client is seeking an experienced

Solution Architect – Data \& AI

with strong expertise in

Azure Data Platforms

to lead the architecture, design, and delivery of modern enterprise technology solutions.

The Solution Architect will be responsible for

designing end-to-end technology solutions

that address complex business requirements and defining the overall

Azure architecture and network design

.

The ideal candidate will have the ability to translate business requirements into

scalable, secure, and high-performing solutions

. The role will also involve establishing the required

architecture, connectivity, security, and integration frameworks

to support enterprise-wide data platforms and AI initiatives.

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 M

icrosoft 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.
• Establish architecture principles, engineering standards and reusable solution patterns.
• 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 architecture integrity throughout the solution lifecycle from design through production deployment.
• Design enterprise data governance solutions leveraging

Microsoft Purview

• Define best practices, reusable assets and mentoring frameworks for internal teams.
• Collaborate with cross-functional teams to

deliver secure, scalable and business-aligned data platform solutions.

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 of experience in Data/AI Solution architecture roles.
• 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