Business Intelligence Engineer @ Amazon · Seattle, WA

Sanket
Thakre

5 years at Amazon building scalable data pipelines, dimensional models, and self-serve analytics platforms on AWS.

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About

Background

Sanket Thakre
Sanket Thakre Business Intelligence Engineer · Seattle, WA

I'm a Business Intelligence Engineer at Amazon in Seattle, five years in. At Amazon, BIE is an analytics and data engineering role: I design and build the pipelines, dimensional models and self-serve reporting that business, finance, operations and external partners run on.

I tend to end up on the systems nobody owns. Two of my main projects were inherited under pressure, both were on fire when I got them, and both are still running. My focus is the full stack from ingestion and transformation through modeling to the BI layer, with an emphasis on reliability, automation and catching a bad number before anyone downstream sees it.

I hold an MS in Computer Engineering from Cal State Fullerton and a BE in Electronics & Telecommunications from the University of Pune. I enjoy working at the intersection of engineering and business, building data systems that actually get used.

📍
Location
Seattle, WA
🏢
Current
BIE @ Amazon
🎓
Education
MS Computer Engineering, CSUF · BE E&T, Pune
✉️
Email
sanket.thakre3@gmail.com
Journey

The Road So Far

2013 - 2018
Grew up in India, studied engineering in Pune
Completed a BE in Electronics & Telecommunications at the University of Pune, where I first got into software and realized I liked building things that worked with data.
Aug 2019
Packed up and moved to the US
Landed in Fullerton, California to start my MS at Cal State Fullerton. New country, new city, new chapter.
2019 - 2021
Graduate school + first US work experience
Finished my MS in Computer Engineering while working as a Graduate Assistant. Got my first taste of professional work in the US supporting university research communications and operations.
Aug 2021
Joined Amazon and moved to Seattle
Got the call from Amazon and made the move to Seattle. Started as a Business Intelligence Engineer in Central Operations, on the fulfillment analytics team, thrown into the deep end from day one, and loved it.
2021 - 2025
Four years building at Amazon scale
Owned end-to-end data systems in Central Operations, from pipelines that run daily FC operations to planning tools used by leadership across NA, EU, Japan, and India. Learned what it means to build for reliability and scale.
Jun 2025 - Present
New team: Amazon Pharmacy
Moved internally to Amazon Pharmacy, into a new domain with real stakes. I own the pipelines and warehouse tables behind contractual partner metrics, plus reporting that pharmacy leadership and regulators depend on. Wrong numbers here cost money, which changes how you build.
Now
Looking for what's next
Five years in, I know what good data infrastructure looks like and what it takes to keep it alive. Now building on the modern stack in my own time: dbt, Airflow, data quality frameworks. Looking for analytics engineering, data engineering or BI engineering roles where I own the pipeline through to the decision. Seattle-based, open to remote or relocation anywhere in the US.
Stack

Technical Skills

Data Engineering
ETL / ELTPipeline MigrationDimensional ModelingStar SchemaSCD TypesData QualityData ContractsMonitoring & Alerting
Languages
SQL (Advanced)PythonPandasNumPyPySparkMatplotlibBash
Cloud & Warehouses
Amazon RedshiftAWS AthenaAWS S3AWS GlueAWS LambdaAWS IAMMySQLPostgreSQL
BI & Visualization
Amazon QuickSightTableauPower BILookerJupyter Notebook
Tools & Practices
GitCode ReviewGitHub ActionsDev / Prod SeparationAgile / ScrumPerformance TuningRoot Cause AnalysisRunbooks & SOPs
Modern Stack · Personal Projects
dbtApache AirflowPostgreSQLDockerGreat Expectations
Built outside work. Three projects on GitHub, linked below.
Experience

Where I've Worked

Amazon
Aug 2021 - Present · Seattle, WA
Business Intelligence Engineer · Pharmacy Jun 2025 - Present
  • Migrated the full performance guarantee reporting stack for two pharmacy benefit manager partners off another org's infrastructure: 12 contractual metrics, 46 ETL pipelines and 24 warehouse tables across dev and prod, plus SFTP delivery to external partners.
  • Repeatedly catch reporting logic errors on contractual metrics before they trigger financial penalties. Audited one after a threshold breach, proved 40 fulfillment errors had been wrongly counted against Amazon, and drove the fix that corrected the quarter.
  • Resolved a Sev-2 contract compliance defect in partner call metrics, correcting the calculation from 100% of calls to the contractual top 80%, then deploying and backfilling history so partner-facing dashboards were accurate.
  • Built the first proactive data quality alerting on metrics carrying financial exposure, where none existed before.
  • Automated the weekly operations speed business review and the daily executive flash report, both previously assembled by hand, delivering a PDF and formula-level Excel workbook to a self-service subscriber list.
  • Launched three QuickSight dashboards on fulfillment learning curves and pharmacy services productivity, used as evidence in State Board of Pharmacy inspections and regulatory accreditation.
  • Built North America kiosk launch analytics, including replenishment and order pipelines giving visibility into kiosk performance across launch markets.
Business Intelligence Engineer · Central Operations Aug 2021 – Jun 2025
  • Took over the model behind Amazon's global fulfillment operational planning weeks before the 2025 annual cycle, when the maintaining team moved orgs. Reverse-engineered nine interconnected stored procedures from a short handover and delivered the cycle on schedule across NA, EU, Japan and India.
  • Diagnosed that system's structural problems, including manual execution triggers, no version control, scattered dashboard queries and minimal documentation, and scoped the modernization plan to address them.
  • Primary developer and product owner for the North America version of the operations alerting platform fulfillment leaders use to manage backlog and customer experience risk, serving 100+ sites. Wrote the original architecture and design document as my first project at Amazon, built the real-time alerting alongside another engineer, and later transitioned it to a new owner.
  • Took over an unowned pipeline feeding shift-level productivity data available in no other source system, with two director escalations open. Resolved the data quality and missing data errors behind them and kept it running; its dashboard saw 30-40K monthly views spanning operations, program, business and director-level users. Still in production.
  • Became the reference point for two BIEs and three business analysts across four regions: wrote the onboarding documentation, ran architecture training, and mentored on stored procedure optimization and data validation.
Cal State Fullerton
Sep 2019 - May 2021 · Fullerton, CA
Graduate Assistant · Office of Research & Sponsored Projects
  • Collaborated with the Associate Vice President to design and produce the department's annual report, making it accessible to a campus community of 45,000+ students and faculty.
  • Maintained department website, managed communications and scheduling, and supported coordination of research workshops and events to promote campus-wide research initiatives.
Education

Academic Background

Cal State Fullerton
MS · Computer Engineering
2019 - 2021 · Fullerton, California
Database Systems Algorithms Software Engineering Graduate Assistant
University of Pune
BE · Electronics & Telecommunications
2013 - 2018 · Pune, India
Digital Systems Signal Processing Software Development Pune, India
Projects

What I've Built

Python dbt Airflow ✓
01
End-to-End ELT Pipeline with dbt & Airflow
PythondbtAirflowPostgreSQLGitHub Actions
9.5M rows of NYC TLC trip data ingested into PostgreSQL, transformed with dbt (staging → intermediate → dimensional mart), orchestrated with Apache Airflow, validated with 22 passing dbt tests, and monitored with Slack alerts. Fully containerized with Docker.
View on GitHub →
Raw Table PostgreSQL GE Checks Null · Schema · Stats Alert ✓ Pass
02
Automated Data Quality & Monitoring Framework
PythonpytestPandasSQL
Custom Python framework for automated data quality monitoring: schema validation, null/duplicate detection, referential integrity checks, and statistical outlier alerting. Generates HTML and JSON reports. 6/6 pytest tests passing, CI via GitHub Actions.
View on GitHub →
Revenue Churn Cohort
03
Self-Serve Analytics Platform for E-commerce
SQLdbtRedshiftQuickSight
Raw e-commerce data → dbt dimensional model → governed metric layer → interactive dashboard (revenue, churn, cohort retention) with documented data lineage.
View on GitHub →
Contact

Let's work together.

I build reliable data pipelines, dimensional models, and analytics platforms that help teams make better decisions. If you're working on something interesting in the data space, grab a time on my calendar and let's talk.

📅 Schedule a Call ✉ Email Me LinkedIn GitHub Tableau