Enhancing Azure Data Workflows at Microsoft

Improving performance, usability, and engagement through a new internal Azure data pipeline.

Role
Software Engineer & Product Manager

Duration
3 Months

Tools
Azure Synapse Analytics, Power BI, SQL, Cubes

Team
Experience & Data

About

At Microsoft, I worked on rethinking how internal teams access and act on Azure cloud data. The original system—built on legacy SQL Cubes—was slow, hard to scale, and difficult to use. Teams needed faster insights and a more intuitive way to engage with cloud usage data.

I helped lead the migration to a modern data pipeline using Azure Synapse Analytics, improving performance, reliability, and access. But I didn’t stop at infrastructure—I also designed interactive Power BI dashboards that made the data actually usable for cross-functional teams. My goal was simple: help people make better decisions, faster.

The Challenge

As Microsoft scaled its cloud infrastructure, teams were struggling with outdated data workflows. The old system created friction for engineers, analysts, and business stakeholders who needed timely insights from Azure usage data. The challenge wasn’t just technical—it was experiential.

We needed a solution that could bridge backend scalability with frontend usability—and align those improvements with real business workflows.

My Role

This was a hybrid role: part engineer, part product thinker. I worked across layers—migrating backend systems while designing frontend tools that people actually wanted to use.

  • Migrated legacy SQL Cubes to Azure Synapse, setting up scalable pipelines and reducing latency

  • Used SQL and custom transformation logic to support real-time refreshes, regression testing, and improved data reliability

  • Designed Power BI dashboards that helped internal teams spot trends, anomalies, and key insights without needing technical deep-dives

  • Built filters, drilldowns, and data storytelling features that made complex data feel intuitive

  • Acted as the mediator between data engineers and product managers—translating needs into implementation specs and cutting unnecessary back-and-forth

  • Contributed to team OKRs by driving improvements in engagement and decision-making efficiency

Why It Matters

As data systems scale, technical debt and latency compound fast. By replacing outdated cube-based infrastructure with a scalable Azure Synapse pipeline, this work reduced friction in how internal teams access and interpret data. This ensures faster refreshes, fewer failures, and a smoother path from raw telemetry to business-critical insights.

Impact

  • Significantly improved processing speed and data reliability

  • Increased internal engagement through intuitive Power BI visualizations

  • Enabled faster, more confident decision-making across internal teams

Want to Learn More?

Due to NDA restrictions, I can’t share full details here, but I’d love to discuss my approach and impact further. Feel free to reach out!

CONTACT & SAY HELLO 💌