Anjali

Data Engineer

Anjali

I build the pipelines that HR analytics runs on. 5 years in data analytics, now building hands-on experience in Fabric and Databricks with metadata-driven pipelines, Delta Lake, and SCD Type 2 dimension management.

  • Microsoft Fabric
  • Databricks
  • Azure Data Factory
  • Delta Lake
  • Power BI
  • SQL
  • PySpark

Currently Sr. Associate, Analytics at Think Talent Services

Portrait of Anjali
5
Years in data analytics
80%
Less manual file processing
55%
Less source query load

Selected work

Case studies

Each one documents the decision, not just the result, including the scenarios that tested whether the design would hold.

  • Power BI
  • 2025

Employee Engagement Survey Dashboard

A Power BI dashboard built on Pierce County, Washington's employee engagement survey. 14,000+ responses cleaned, modelled and shaped into role- and department-level analysis with bookmark-driven navigation.

  • Microsoft Fabric
  • Data Factory
  • 2026

The Global Listing Intelligence Initiative

An end-to-end Microsoft Fabric solution for a global luxury real-estate company, automating property listing ingestion from London, Dubai and New York into a governed Silver layer with wildcard matching, upsert logic and automated archival.

  • Microsoft Fabric
  • Delta Lake
  • 2026

Logistics Data Modernization

A Microsoft Fabric case study in watermark-based incremental ingestion of high-volume JSON shipment logs, replacing manual file selection with auditable state management and Delta Lake ACID writes.

All 12 case studies →

Experience

Where I've done this

  1. 07/2022 – Present

    Current

    Sr. Associate, Analytics

    Think Talent Services

    • Built a medallion (Bronze-Silver-Gold) pipeline on Microsoft Fabric using Data Factory to ingest and consolidate internal and external partner assessment data, processing millions of records and cutting manual file processing by 80%, delivering analysis-ready Gold-tier datasets that powered 9-box potential mapping and new-hire benchmarking.
    • Built a metadata-driven pipeline framework using ForEach activities with dynamic content expressions, reading source table configurations from a control Delta table, simplifying onboarding of new talent data sources (LMS, performance management system, assessment platforms) without pipeline code changes.
    • Designed SCD Type 2 dimension management for dim_employee and dim_position using Delta MERGE, preserving 2 years of historical career and role change history (promotions, transfers, band changes) with is_current flags and start/end date assignment for point-in-time reporting.
    • Built ADF batch pipelines to ingest daily performance, engagement, and hiring data from 3 business units into Azure SQL staging tables, feeding Power BI Premium semantic models refreshed each morning for 15 HRBPs and talent leads.
  2. 03/2022 – 06/2022

    Intern

    Think Talent Services

    • Streamlined reporting pipelines and enhanced analytics by implementing Excel M-Query and DAX.
    • Reduced team reporting workload by 4 hours weekly through the creation of macro-enabled templates.
    • Boosted client engagement by 11% with the development of an interactive Power BI dashboard.
  3. 06/2021 – 03/2022

    Statistics Tutor

    Tutor Eye

    • Executed Exploratory Data Analysis (EDA) using Python to extract valuable data insights, directly contributing to improved student performance and educational success.

Full background, education and certifications →

Toolkit

What I work with

Microsoft Fabric

  • Data Factory
  • Lakehouse
  • Warehouse
  • OneLake
  • Dataflow Gen2
  • Tumbling window triggers
  • ForEach
  • Direct Lake
  • Monitoring Hub

Azure Data Factory

  • Metadata-driven pipelines
  • ForEach
  • Copy activity
  • Event-based triggers
  • Linked services
  • ADLS Gen2
  • Azure SQL

Delta Lake

  • Liquid Clustering
  • Z-Ordering
  • Partitioning
  • OPTIMIZE
  • VACUUM
  • MERGE
  • Time travel
  • V-Order
  • SCD Type 2

Power BI, DAX and Excel

  • Semantic models
  • DAX measures
  • Power Query (M)
  • Power BI Dataflows Gen1
  • Incremental refresh
  • Row-level security
  • Advanced Excel

Python, PySpark and SQL

  • Python
  • Databricks
  • Window functions
  • AQE
  • Broadcast joins
  • Predicate pushdown
  • T-SQL MERGE
  • CTEs
  • Dynamic content expressions

Data Modelling

  • Star schema
  • SCD Type 2
  • Accumulating snapshot facts
  • 3NF to Gold denormalisation