The Data Test Engineering (DTE) team is responsible for protecting the quality and integrity of analytics data throughout its complete lifecycle — from events generated by web, mobile, and connected TV applications through ingestion, transformation, data warehouses, and downstream reporting. This is not a traditional QA role. We are looking for a hands-on Senior Data Test Engineer who combines end-to-end data reasoning, analytics validation, automation engineering, and strong troubleshooting skills. You will work across client applications and backend data systems, helping replace repetitive manual validation with scalable automation while supporting frequent releases across a large-scale digital platform.
Validate analytics events generated across web, mobile, and connected TV applications.
Test analytics data end to end, from client-side event generation and ingestion through transformation, warehouse storage, and downstream reporting.
Verify event payloads, sequencing, business rules, transformations, and final database records.
Use SQL to investigate anomalies, troubleshoot data-quality issues, and validate data in BigQuery.
Build and maintain reusable automation for client analytics, backend systems, and data-pipeline validation.
Contribute to an existing Java-based automation framework, while applying automation principles that can be transferred across programming languages.
Expand automated regression coverage and reduce reliance on repetitive manual testing.
Perform exploratory testing when needed and identify opportunities to convert repeatable validation into automation.
Troubleshoot issues across client applications, ingestion systems, transformation layers, and warehouse tables.
Support frequent releases, hotfixes, platform rollouts, and production issue investigations.
Collaborate with engineering, product, data, and reporting teams to investigate issues and drive them through resolution.
Use AI-assisted engineering tools responsibly to improve planning, test development, and troubleshooting while independently reviewing and validating their output.
Contribute across both client-side analytics and backend data systems according to team priorities.
O que esta busca pede
Competências da vaga. Imprescindível é o que a posição precisa; diferencial soma, mas não substitui.
QA · mínimo 3 anosTest Engineering · mínimo 3 anosData Quality Engineering · mínimo 3 anosSQL · mínimo 3 anosBigQuery · mínimo 3 anosJava · mínimo 3 anosPython · mínimo 3 anos.NET · mínimo 3 anosInglês · mínimo Avançado · imprescindível
O que a posição pede no dia a dia
- +5 years of experience in QA, Test Engineering, Data Quality Engineering, or a related discipline, including 3+ years focused on data pipelines, data warehouses, or analytics validation.
- Strong understanding of end-to-end data flows, including event generation, ingestion, transformation, warehouse storage, and reporting.
- Strong SQL skills and hands-on experience validating data in BigQuery or a comparable cloud data warehouse.
- Strong test automation experience, including building or contributing to reusable automated testing or data-validation frameworks.
- Experience validating analytics implementations across web, mobile, OTT, or connected TV applications.
- Ability to verify event payloads, event sequencing, transformations, and business rules across multiple system layers.
- Proficiency in at least one relevant programming or scripting language, such as Java, Python, or .NET.
- Strong debugging and root-cause analysis skills across client applications and backend data systems.
- Strong communication and critical-thinking skills, including the ability to ask clarifying questions and work through ambiguous problems collaboratively.
- Ability to work consistently during US-aligned business hours.
Requisitos
- Experience contributing to Java-based automation frameworks.
- Experience using Python for automation, data validation, or cloud-related workflows.
- Experience with Selenium WebDriver, Appium, Page Object Model, device farms, or comparable cross-platform automation tools.
- Experience with CI/CD workflows using Jenkins or GitHub Actions.
- Experience supporting streaming media, high-volume analytics, or multi-platform consumer applications.
- Experience using AI-assisted development or testing tools as part of a reviewed engineering workflow.