Senior SDET · Data Quality · Toronto, Canada

Chris Yoon. Senior SDET. Data Quality.

10+ years across QA, test automation, and data quality — most recently Data QA Architect at theScore, where I designed the QA regression framework (Airflow, Python, SQL) that guarded millions of daily betting transactions across BigQuery and Redshift. I design and operate the automation frameworks and quality controls that let teams ship data they can trust.

See experienceLinkedIn
qa_regression — daily run

$ airflow dags trigger qa_regression

✓ 15+ ETL workflows validated

✓ reconciliation: source ↔ target matched

✓ dq gates: all green — no corrupt data shipped

Experience

10+ years

QA, SDET / test automation, and data quality — Expedia, QA Consultants, theScore.

Most recently

Data QA Architect

theScore (2023–2025) — Airflow QA regression framework promoted to production; SOX-facing reconciliation.

Based in

Toronto, Canada

Open to Toronto/GTA and Canada-remote roles. Korean (native) · English (fluent).

Experience

Where I've worked, what I owned.

Data QA Architect · theScore

Jul 2023 — Jun 2025

  • Proposed, designed, and implemented a QA regression DAG in Apache Airflow — promoted to production — running parallel Python/SQL validation checks across 15+ ETL workflows.
  • Operated Airflow pipelines across BigQuery and Redshift processing millions of daily sports-betting transactions, including bets placed at self-service retail kiosks, validated from terminal to backend.
  • Built source-to-target reconciliation with critical-failure gates and real-time Slack alerting, so corrupt or incomplete data never reached downstream reporting.
  • Delivered SQL/Python reconciliation pipelines for SOX-facing financial and regulatory reporting, with audit-ready exception handling and release evidence.

Tech Lead · QA Consultants

Apr 2021 — Mar 2023

  • Led a five-person data quality team delivering data-migration automation for health-claims data.
  • Designed a QA framework for scanned extended-health claims collected across multiple U.S. states — template comparison, field normalization, and promotion to a validated gold layer in GCP.
  • Built Python and SQL automation suites that bulk-processed legacy PHI claims into clean, verified datasets for client handoff.

Data QA Team Lead · QA Consultants

Feb 2020 — Apr 2021

  • Led a three-person QA team embedded within Data Engineering during an enterprise AWS-to-GCP migration spanning four data business units.
  • Established source-to-target SQL reconciliation pipelines and automated ETL validation at daily checkpoints, validating millions of delivered records.
  • Supplied the concrete test evidence used for final release sign-off.

QA & Data Migration Roles · Avesis · Expedia Group · Wisetail

2014 — 2020

  • Data-migration automation at Avesis, moving scanned health-related data from multiple states into GCP.
  • Software QA roles at Expedia Group and Wisetail — the foundation in test design and automation that everything since builds on.

QA since 2014 · ISTQB CTFL certified · Chemical Engineering studies, University of Waterloo · Korean (native) · English (fluent)

Skills

What I work with.

Test Automation

PlaywrightSeleniumPythonPytestAPI TestingE2E TestingTest StrategyCI/CD Gates

Data Quality & Reliability

SQLApache AirflowETL/ELT ValidationSource-to-Target ReconciliationDQ GatesSchema DriftData ObservabilitySOX Reporting Controls

Data Platforms & Cloud

BigQueryRedshiftPostgreSQLGCPAWSDocker

Engineering & Delivery

JenkinsGitHub ActionsGitFastAPITypeScriptNext.js

Leadership

Team LeadershipQA StrategyMentoringRelease Sign-offStakeholder Reporting

Work

Active build

Building

OPB Poker

Personal project: a poker performance backend with a three-layer data pipeline (raw → normalized → derived) over an entity-centric PostgreSQL schema. TDD-first build with deterministic output contracts, Pytest regression suites, and operator QA gates.

  • Ingestion pipeline treats each upload as a session packet: parsed, deduplicated, and reconciled into canonical truth before any derived layer runs — provenance preserved end-to-end.

  • Entity-centric PostgreSQL schema: player, session, tournament, hand, pattern, and intervention as first-class entities. Raw, normalized, and derived layers kept separate and independently queryable.

  • TDD-first across the full stack: output contracts defined before implementation, Pytest regression suite from ingestion through runtime serving, Playwright E2E on the consumer surface.

onepercentbetter.poker
Python
PostgreSQL
psycopg2
Pytest
Playwright
Supabase
Next.js
TypeScript

A OnePercentBetter project

The Closing Line

Grading the closing lines of the world's prediction markets.

Explore project →

Proof of Work

1% Better - This WebsiteNext.js, TypeScript, Vercel
Blue Jays Moneyball ETLPython, Apache Airflow, PostgreSQL
TwelveLabs API ValidatorPython, TwelveLabs, Pytest

About

Chris S. Yoon

Senior SDET and Data Quality engineer with 10+ years across QA, test automation, and data reliability. Most recently Data QA Architect at theScore; before that, Tech Lead of a five-person data quality team at QA Consultants. My work is designing the frameworks and controls that prove software and data are correct — not just testing inside someone else's.

Open to Senior SDET · QA Automation · Data Quality · QA Lead roles

Recruiter path

Experience first, then proof.

Start with where I've worked and what I owned, then the projects that show how I build. Toronto-based; open to GTA and Canada-remote roles.

Read experienceOpen LinkedInsukminc@gmail.com