Shakti Singh.

Overview

Engineering workflows supporting Microsoft Fabric capacity and usage analytics, from telemetry processing to analytical consumption.

Problem

Capacity analysis requires reliable telemetry, historical context, and a clear view of usage across workloads.

My Contribution

Designed data engineering workflows for capacity analytics and historical data handling. Built Fabric Rayfin, an application on Power BI reports, with provisioned CU trends and Lakehouse-versus-Kusto workload comparisons.

Architecture

Technology

Microsoft Fabric · Azure Synapse · SQL · PySpark · Power BI

Impact

Enabled interactive exploration of capacity utilization, provisioned compute trends, and workload comparisons.

Key Learnings

• Historical context is essential to interpreting utilization.
• Workload comparisons make capacity patterns easier to investigate.

Overview

Privacy and compliance automation supporting GDPR entity processing across multiple data systems.

Problem

Cross-system privacy workflows require consistent handling, timely action, and dependable operational oversight.

My Contribution

Owned GDPR privacy and compliance automation. Built and improved entity-processing workflows, alongside automation for compliance and change-management tasks.

Architecture

Technology

Azure · Microsoft Fabric · Kusto · Cosmos DB · ADLS

Impact

Supported audit-ready compliance operations and timely privacy actions through automation and ownership.

Key Learnings

• Privacy workflows require both automation and operational ownership.
• Consistency matters across every participating data system.

Overview

Data curation and telemetry engineering that transforms raw events into reusable analytics datasets and executive-ready metrics.

Problem

Platform adoption is difficult to understand without consistent, trustworthy metrics derived from large-scale event data.

My Contribution

Delivered a Monthly Active Users analytics product end to end, from requirements to reusable scripts and configuration-driven mappings. Developed reusable ETL/ELT patterns and source-to-target reconciliation mechanisms.

Architecture

Technology

Microsoft Fabric · Azure · Kusto · ETL / ELT

Impact

Enabled leadership to track platform adoption and established foundations for adoption-funnel measurement.

Key Learnings

• Metric definitions need clear business requirements.
• Reusable mappings support consistent analytics as usage evolves.

Overview

A concept for helping engineers interpret capacity signals and identify areas that deserve deeper investigation.

Problem

Capacity signals need engineering context before they can inform useful optimization decisions.

My Contribution

Concept direction: bring together capacity analysis and AI assistance to help engineers explore potential optimization opportunities. Presented as a proposed approach, not an implemented system.

Architecture

Technology

Proposed: AI · Microsoft Fabric · Workflow automation

Impact

Intended outcome: assist engineers in identifying optimization opportunities. No deployment, cost savings, or measured results are claimed.

Key Learnings

• Design consideration: recommendations need supporting evidence.
• Design consideration: optimization decisions should remain engineer-reviewed.

Overview

Exploration of AI-assisted engineering and agent connectivity for modern data-platform workflows.

Problem

Repetitive investigation and platform tasks take engineering time and require context across different tools.

My Contribution

Applied GitHub Copilot and agentic approaches in engineering and incident-response workflows. Built a Fabric MCP server exposing tools for lakehouse queries, pipelines, semantic models, and capacity metrics.

Architecture

Technology

AI agents · Microsoft Fabric · Azure · MCP · GitHub Copilot

Impact

Enabled natural-language data operations through the Fabric MCP interface. Broader agent-driven operational automation remains exploratory; no quantified productivity outcome is claimed.

Key Learnings

• Structured tools connect agents to useful platform capabilities.
• Design consideration: agent assistance needs clear access boundaries.

Overview

Operational engineering supporting reliable enterprise data platforms and dependable production workflows.

Problem

Pipeline failures and production incidents need timely investigation, clear accountability, and cross-team follow-through.

My Contribution

Served as a production data-platform on-call owner in a follow-the-sun rotation. Resolved incidents, drove root-cause analysis across partner teams, and automated slow-query diagnostics and operational workflows.

Architecture

Technology

Azure · Azure Synapse · Monitoring · SQL · Kusto

Impact

Supported production reliability through incident ownership, root-cause analysis, and repeatable diagnostics.

Key Learnings

• Production reliability depends on ownership across team boundaries.
• Repeatable diagnostics reduce repeated manual investigation.