Shreyansh Dubey Data & Analytics Engineering

About

Data & Product
Analytics

Professional summary

I'm a Senior Data & Analytics Engineer with around 5.5 years of client delivery, and most of that work had the same shape: a business problem data could answer, and nothing in place to answer it.

I've delivered enterprise BI, financial analytics, product analytics and automation across banking, wealth and asset management, travel, healthcare and manufacturing. The work usually started in a requirements conversation with finance, operations or product leadership and ended in something people ran their week on.

Technically that spanned the full stack: SSIS and SQL Server ETL, Power BI semantic models and advanced DAX, behavioural data engineering on Azure Databricks with PySpark, and modern lakehouse architecture on Microsoft Fabric and OneLake. I led two concurrent engagements across 17 engineers, owning target-state architecture, KPI standardisation, semantic-model governance and the stakeholder relationship that went with them.

The part I care most about is the translation layer — turning a business requirement into a measurement model, a governed definition and a system that stays trustworthy after I've handed it over.

Full resume

Portrait of Shreyansh Dubey

By the numbers

  • 5.5+ years of client delivery
  • 17 engineers led across two concurrent engagements
  • 13 clients worked with
  • 50+ dashboards shipped

Capabilities

What I work with

Product & business analytics

  • Funnel analysis
  • Retention & cohort analysis
  • Churn modeling
  • KPI design
  • Event tracking definition
  • Requirements gathering
  • Stakeholder management
  • Financial & wealth analytics
  • Operational & SLA reporting

BI & semantic modeling

  • Power BI
  • Advanced DAX
  • Power Query
  • Semantic modeling
  • Star schema
  • Row-level security
  • SSRS / paginated reports
  • Embedded & executive dashboards
  • Report performance tuning

Data engineering & platform

  • Microsoft Fabric
  • OneLake
  • Lakehouse architecture
  • Azure Data Factory
  • Azure Databricks
  • PySpark
  • Synapse
  • SSIS
  • ETL / ELT design
  • Data governance

Automation & Power Platform

  • Power Automate
  • Power Apps
  • Microsoft Dynamics
  • SharePoint
  • Alteryx
  • REST APIs
  • Azure Key Vault
  • CI/CD (GitHub Actions)

Data & SQL

  • Advanced SQL (T-SQL)
  • SQL Server
  • Data modeling
  • Query optimization
  • Data warehousing
  • Data cleansing & validation
  • Python / Pandas

Ways of working

  • Agile / Scrum
  • Git
  • Client-facing delivery
  • Technical leadership
  • Mentoring (10+ engineers)

Domains

Where the work happens

  • Banking
  • Wealth & Asset Management
  • Consumer SaaS
  • Travel
  • Healthcare
  • Manufacturing