Data & AI Cloud Solution Architect- Private Equity Technology Advisory

ALYSIAN- TECH M&A- DATA & AI CLOUD SOLUTION ARCHITECT
JOB TITLE:
Principal
LOCATION:
Existing hubs are in Delhi NCR (Noida and Gurgaon) – preference, alternative preferred option includes Mumbai
WORK ARRANGEMENT:
Hybrid
EMPLOYMENT TYPE:
Permanent
CONTEXT ON ROLE
We are seeking an experienced Data and AI Cloud Solution Architect to lead design and implement enterprise-scale cloud data and AI solutions using Microsoft Fabric, Azure Databricks, and the broader Azure ecosystem. This role requires a proven solution architect with extensive Microsoft technology expertise who will lead customer engagements, design scalable cloud architectures, and drive the adoption of modern data and AI platforms while ensuring seamless integration between IES Gateway and our analytics ecosystem.
The Data and AI Senior Cloud Solution Architect will help clients use cloud technology, data engineering, and AI/ML to improve how they manage and use data. They will design solutions that transform data systems and enable large-scale use of advanced analytics and generative AI.
KEY ATTRIBUTES & EXPECTATIONS
Operates at a very rapid pace to deliver high-impact outcomes in fast-moving environments.
Able to work with incomplete information, applying intelligence, experience, and sound judgment to fill gaps and make informed decisions.
Takes full ownership of deliverables, ensuring they provide the best possible value to the client- which may involve challenging initial requests and steering towards more effective solutions.
Confident engaging with all levels of a client’s organization, from team leads to executives, efficiently gathering relevant information and presenting insights with clarity, authority, and the appropriate level of gravitas for senior audiences.
Committed to building reusable assets and operating efficiencies within their specialism, contributing to Alysian’s broader capability and intellectual capital.
Consistently seeks and drives solutions that deliver value aligned with Private Equity expectations — recognizing that these priorities may differ from long-term business goals, as PE ownership may focus on rapid, short-term improvements that enhance sale value
Comfortable challenging established thinking and influencing stakeholders at all levels by presenting alternative solutions supported with robust financial, operational, and technical justifications
RESPONSIBILITIES
Solution Architecture & Design
Lead solution design sessions with stakeholders to translate business requirements into technical architectures
Design comprehensive cloud data and AI solutions for data engineering, data lakes, analytics, and AI/ML use cases leveraging Microsoft Fabric, Azure AI Services, and Azure Machine Learning
Define target architectures and roadmaps for AI/data platforms (e.g., Lakehouse, MLOps)
Create scalable, secure, and cost-effective cloud solutions that meet enterprise requirements
Architect end-to-end data and AI platforms that integrate seamlessly with customer environments
Select and configure tools and technologies across the data & AI stack: ingestion, storage, processing, modelling, and serving
Develop reference architectures and best practice guidelines for data and AI implementations
Customer Engagement & Technical Leadership
Serve as the primary technical advisor for cloud data strategy and complex data and AI solution implementations
Lead technical discussions with customer architects, engineers, and business stakeholders
Conduct solution workshops, proof-of-concepts, solutions demos and technical deep-dive sessions
Provide technical guidance during pre-sales activities and solution validation
Mentor and guide implementation teams on Microsoft best practices and architectural patterns
Microsoft Fabric & Azure Databricks Platform Expertise
Design and implement Microsoft Fabric solutions including OneLake, Data Factory, and Synapse Analytics.
Architect data flows, integration patterns, and analytics workspaces within the Fabric ecosystem.
Establish Power BI integration patterns and advanced analytics frameworks.
Design and configure Azure Databricks clusters, workspaces, and job orchestration for enterprise-scale data processing.
Implement performance tuning strategies for Azure Databricks including Spark optimization, cluster autoscaling, and resource management.
Configure Azure Databricks security patterns including workspace isolation, access controls, and network security.
Implement modern data lakehouse architectures using Delta Lake with integrated AI/ML capabilities.
Design Azure Databricks integration patterns with Microsoft Fabric for seamless data flow and analytics.
Data Integration & AI Platform Implementation
Design sophisticated data integration patterns between IES Gateway and cloud analytics platforms using Azure Databricks and Microsoft Fabric.
Architect Delta Lake implementations optimized for IES Gateway data workflows with advanced partitioning and performance tuning.
Implement medallion architecture (Bronze/Silver/Gold layers) using Azure Databricks with embedded AI/ML processing capabilities.
Create real-time data ingestion patterns using Azure Databricks structured streaming and Delta Live Tables.
Design scalable data pipelines using Azure Databricks for complex ETL/ELT processes and real-time data integration.
Establish MLOps pipelines and AI model deployment patterns using Azure Databricks Machine Learning and Azure Machine Learning integration.
Implement Azure Databricks workflows for automated data quality monitoring and data governance processes.
Design and implement data governance frameworks using Microsoft Purview with integrated Azure Databricks lineage tracking.
Security, Governance & Compliance
Architect comprehensive security patterns aligned with federal and state requirements for sensitive data and AI systems
Design secure data architectures on Azure with a strong understanding of cloud identity and access management (IAM) - including role-based access control (RBAC), attribute-based access control (ABAC) and principle of least privilege – and securing data at rest and in transit with cloud key management services implement advanced authentication, authorization, and data protection mechanisms
Establish data classification and tagging strategies (e.g., PII, PHI, PCI), encryption standards (AES-256, TLS, HMAC) across structured and unstructured data and data loss prevention (DLP) and tokenization solutions
Implement compliance frameworks such as GDPR, HIPAA, SOC 2, ISO 27001, CCPA
Design audit logging, monitoring, and compliance reporting frameworks
Establish responsible AI practices and governance frameworks for machine learning operations
Configure Microsoft Purview for data lineage, quality monitoring, and AI model governance
Performance Optimization & Innovation
Implement performance tuning strategies for large-scale data processing, analytics, and AI workloads
Optimize Azure resource utilization and cost management across data and AI services
Design intelligent caching, partitioning, and scaling mechanisms for cloud-native architectures
Establish comprehensive monitoring and alerting frameworks for data and AI operations
Drive innovation by evaluating and integrating emerging Microsoft data and AI services
REQUIRED QUALIFICATION
Bachelor's degree in Computer Science, Information Technology, Data Engineering, or related field
12+ years of progressive experience in cloud solution architecture with focus on data and AI platforms
4+ years of experience working as a Cloud Solution Architect or Data Architect specifically within Microsoft technology environments
2+ years hands-on production experience with Azure Databricks, Apache Spark, and Azure Machine Learning
Current hands-on experience with Microsoft Fabric platform, Azure AI Services, and Azure Databricks advanced features (Delta Live Tables, MLflow, Databricks SQL)
Proven track record of leading customer-facing technical engagements and solution design sessions
Deep expertise in Azure Databricks architecture including workspace management, cluster optimization, and integration patterns
Experience with cloud data architecture patterns including data lakes, data warehouses, lakehouses, and Delta Lake implementations
Experience with AI/ML solution architecture including model deployment, MLOps, and responsible AI practices
Strong knowledge of Azure ecosystem including Azure Data Factory, Azure Synapse Analytics, Azure Cognitive Services, and Azure OpenAI
TECHNICAL EXPERTISE
Microsoft Fabric:
OneLake, Data Factory, Synapse Analytics, Power BI, Data Activator
Azure AI Platform:
Azure Machine Learning, Azure Cognitive Services, Azure OpenAI, Azure AI Search
Data Processing & Analytics:
Azure Databricks (cluster management, job orchestration, performance optimization), Apache Spark, Delta Lake, Delta Live Tables, structured streaming analytics
Integration & Orchestration:
Azure Data Factory, Logic Apps, Event Hubs, Service Bus, Azure Databricks workflows
Governance:
Microsoft Purview, Azure Policy, security and compliance frameworks
Programming:
Python, SQL, Spark SQL, KQL (Kusto Query Language)
AI/ML:
Machine learning model development, MLOps pipelines, responsible AI practices

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