Engineer Workspace

BuildingAnalytics PlatformsNot Just Dashboards.

Welcome to my engineering workspace.

I design analytics systems that transform raw operational data into trusted business decisions through scalable data pipelines, dimensional modeling, semantic layers, cloud architecture, and AI-powered analytics.

9+

Years

25+

Enterprise Projects

10+

Core Platforms

4

Project Deep Dives

Explore Projects Download Resume

Platform Blueprint

From raw signals to trusted decisions

Ingestion

Designed for reliability, scale, and explainability.

Modeling

Designed for reliability, scale, and explainability.

Semantic Layer

Designed for reliability, scale, and explainability.

Governance

Designed for reliability, scale, and explainability.

Output

Decision-ready analytics products

Featured Projects

Case studies for systems thinkers.

Every project below represents a real analytics platform I have designed or engineered, from enterprise BI ecosystems to AI-powered analytics products.

MetricMend

AI Analytics Platform

Natural language analytics platform that transforms business questions into trusted insights.

Next.jsDatabricksSemantic LayerAI

Open Project

AWS Lakehouse

Cloud Analytics

Modern AWS analytics architecture using S3, Athena, Glue, Lake Formation and QuickSight.

AthenaGlueS3QuickSight

Open Project

Enterprise BI

Promethean World

Power BI, AZURE, Fabric, dimensional modeling, and self-service analytics platform.

Power BIAZUREFabricDAX

Open Project

BI Modernization

KinderCare Education

Power BI, SSIS, SQL Server, dimensional modeling, and self-service analytics platform.

Power BISQL ServerSSISDAX

Open Project

Toolchain

The stack is broad because the work crosses layers.

I like owning the path from raw data to usable product. That means the engineering, modeling, governance, and user experience all have to be designed together.

Data Platforms

AWSAzureDatabricksFabricSnowflake

Analytics Engineering

SQLdbt patternsDimensional modelingSemantic layers

BI Products

Power BITableauQuickSightExecutive reporting

Product Engineering

Next.jsReactTypeScriptAPI integration

AI Analytics

Natural language UXMetric retrievalInsight generation

Delivery Practices

Git workflowsDocumentationStakeholder demos

Source

Operational systems, files, APIs

Model

Cleaned facts, dimensions, metrics

Govern

Definitions, lineage, access control

Serve

BI, embedded analytics, AI experiences

Engineering Principles

How I Approach Every Project

Tools change. Frameworks evolve. Good engineering principles do not. These ideas guide every analytics platform I build.

Business First

Every technical decision starts with understanding the business problem, not the technology.

Automate Everything

Manual processes eventually fail. If something repeats, it belongs in an automated pipeline.

Single Source of Truth

Reliable analytics begin with trusted data models, governed metrics, and consistent business definitions.

Build for Scale

Architect solutions that continue to perform as data volume, users, and business complexity grow.

Think in Systems

Great analytics is an ecosystem of ingestion, modeling, governance, visualization, and decision-making.

Keep Learning

Technology evolves quickly. I enjoy exploring AI, cloud platforms, and modern analytics engineering practices.

Connect

Need someone who can think in data systems and ship the product?

I am strongest where analytics engineering, cloud architecture, semantic modeling, and stakeholder clarity meet.

Email Akhil Download Resume

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