Hiring for a Client - Vortiqo Technologies

Roles & Responsibilities

1. Design end-to-end data architecture on Azure covering ingestion, storage, transformation, governance, and consumption layers
2. Define reference architectures using Azure Data Lake, Azure Synapse Analytics, Microsoft Fabric, Azure Databricks, and Azure SQL/Cosmos DB
3. Architect AI/ML and Generative AI solutions using Azure Machine Learning, Azure AI Foundry, Azure OpenAI Service, and Cognitive Services
4. Design data governance, security, and compliance frameworks using Microsoft Purview, Unity Catalog, and Azure security best practices
5. Create solution blueprints, high-level and low-level design documents, and target-state architecture diagrams
6. Partner with sales teams on customer discovery calls to understand current data landscape, pain points, and business goals
7. Lead technical solutioning for RFPs/RFIs, prepare architecture proposals, effort estimates, and delivery roadmaps
8. Deliver architecture presentations, PoCs, and demos to technical and business stakeholders
9. Support commercial teams with technical positioning of Azure Data & AI offerings against customer requirements
10. Provide hands-on architectural oversight during implementation, ensuring adherence to design and Azure best practices
11. Guide data engineering and data science teams on pipeline design, data modeling, MLOps, and deployment patterns
12. Review code, pipelines, and infrastructure-as-code for architectural compliance, performance, and cost optimization
13. Troubleshoot complex technical issues and provide escalation support during critical project phases
14. Mentor engineers and consultants on Azure data platform and AI capabilities





Ideal Candidate 1 Strong Azure Data & AI Architect Profile with pre-sales solutioning and hands-on delivery leadership

2 Mandatory (Experience 1): Must have 10+ years overall, with 8+ years in Azure Data/AI architecture, and proven experience architecting and delivering large-scale data platforms on Microsoft Azure

3 Mandatory (Experience 2 ): Must be able to design end-to-end Azure data architecture (ingestion, storage, transformation, governance, consumption), create reference architectures, and produce solution blueprints, HLD/LLD, and target-state diagrams.

4 Mandatory (Experience 3): Must have pre-sales experience — customer discovery, technical solutioning for RFPs/RFIs, architecture proposals, effort/cost estimation, delivery roadmaps, and architecture presentations/PoCs/demos.

5 Mandatory (Experience 4 ): Must have provided hands-on architectural oversight during delivery (Well-Architected Framework), guiding data engineering/science teams on pipeline design, data modeling, MLOps, and deployment, and reviewing code/pipelines/IaC for compliance, performance, and cost

6 Mandatory (Experience 5 – Microsoft Partner): Must have prior experience in a Microsoft Partner organization, with direct involvement in achieving/maintaining the Data & AI (Azure) Solutions Partner designation,



and hands-on contribution to passing the Microsoft Data & AI specialization audit (customer success references, skilling, performance evidence)

7 Mandatory (Tech skill 1): Must have strong expertise in Azure Data Lake Storage, Azure Synapse Analytics, Microsoft Fabric, and/or Azure Databricks.

8 Mandatory (Tech skill 2): Must have experience with Azure Machine Learning, Azure OpenAI Service, and building AI/ML or GenAI-powered solutions (Azure AI Foundry, Cognitive Services).

9 Mandatory (Tech skill 3): Must have a solid understanding of ETL/ELT pipelines, data modeling (dimensional / data vault), and orchestration tools (Azure Data Factory, Synapse Pipelines).

10 Mandatory (Tech skill 4): Must have familiarity with Microsoft Purview (or equivalent) for data governance, cataloging, and lineage, plus working knowledge of Azure security, networking, and identity (Entra ID, Private Link, Key Vault, RBAC)

11 Mandatory (Tech skill 5): Must have hands-on scripting/programming in Python, SQL, and/or Spark, and IaC experience (Bicep, ARM templates, or Terraform) for provisioning Azure resources.

12 Mandatory (Communication): Must have strong client-facing communication, able to present architecture to both technical and executive audiences.

13 Preferred (Certifications): Azure Solutions Architect Expert, Azure Data Engineer Associate, Azure AI Engineer Associate, or DP-600 (Fabric Analytics Enginee

14 Preferred (Other): Power BI semantic modeling/reporting; MLOps tools (MLflow, Azure ML pipelines, CI/CD for ML); consulting / SI / Microsoft-partner (Solutions Partner) setting experience

📌 Azure Architect – Data & AI (India)
🏢 TalentXO
📍 India