Modern Data Engineering & AI Solutions on Azure
KLOUD17 helps businesses design scalable cloud data platforms, AI solutions, and enterprise analytics using Microsoft Azure technologies.
Consultancy services
Hands-on engineering expertise across the modern Azure data and AI stack — from architecture design through to production delivery.
Data Engineering
ETL/ELT pipelines, lakehouse design, and modern data platforms on Azure Data Factory, Microsoft Fabric, Databricks, and Synapse.
- Pipelines & orchestration
- Lakehouse architecture
- Streaming
AI & Machine Learning
Production-grade GenAI on Azure OpenAI — copilots, RAG, document intelligence, and AI automation grounded in your data.
- Azure OpenAI
- RAG architecture
- AI copilots
Cloud Architecture
Azure migration and platform modernization with security, scalability, and cost discipline designed in from day one.
- Azure migration
- Platform modernization
- Cost optimization
Analytics & BI
Power BI dashboards, executive KPI platforms, and reporting automation backed by a governed semantic layer.
- Power BI
- Executive dashboards
- Reporting automation
The stack I work with
Deep, daily-driver expertise across the Microsoft data and AI platform — and the broader modern data stack.
Microsoft
- Azure
- Microsoft Fabric
- Synapse
- Data Factory
- Power BI
- Azure OpenAI
- Functions
- Logic Apps
Data
- Databricks
- Spark
- Delta Lake
- Python
- SQL
- Kafka
- Snowflake
DataOps
- GitHub Actions
- Azure DevOps
- Terraform
- Docker
- CI/CD
Latest from the blog
Practical guides, architecture patterns, and notes from real Azure and AI engagements.
From OneLake to Agents: Building Modern Data & AI Solutions on Azure
A technical walkthrough of building end-to-end Data & AI solutions on Azure with Microsoft Fabric, OneLake, and Microsoft Foundry — from governed data to production agents.
Read post →ArchitectureBuilding a Modern Lakehouse on Azure
An architecture walkthrough of a production-grade Azure Lakehouse — medallion layout, Delta Lake, governance, and the design choices that matter.
Read post →Azure Data EngineeringAzure Data Factory Best Practices for Production Pipelines
Patterns for building reliable, observable, and cost-efficient ADF pipelines — covering parameterization, integration runtimes, error handling, and CI/CD.
Read post →Have an Azure or AI project in mind?
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