Mattel
toy and family entertainment
QualityAssurance(QAEngineer)
Neural analysis suggests this role is
optimal for mid candidates.
“Quality Assurance (QA Engineer) at Mattel. Skills: consumer data validation, data pipeline testing, SQL, BI tool validation. Validate consumer identity, profile, behavioral, and transactional data across all layers of the data platform.. Perform end-to-end dataset comparisons.”
What You'll Achieve.
ensure consumer-level records, counts, and attributes remain consistent as data moves through ingestion and transformation layers; reconcile consumer metrics and KPIs displayed in Tableau and ThoughtSpot dashboards against upstream source and warehouse tables; identify issues such as duplication, data loss, mis-joins, or incorrect consumer rollups; contribute to the continuous improvement of consumer data QA standards, validation frameworks, and automation coverage
Industry & Context.
analytical and troubleshooting skills
What They're Looking For.
Must Have
2–5 years of QA experience focused on consumer data, analytics, or business intelligence., Proficiency in SQL for validating consumer-level datasets (e. g. , Google BigQuery or similar platforms)., Hands-on experience testing data pipelines within modern data lake or warehouse architectures., Proven experience validating consumer-focused dashboards and metrics in BI tools., Solid understanding of consumer data models, including identity resolution, event data, and transactional facts., Experience using defect tracking and test management tools such as JIRA., Analytical and troubleshooting skills with exceptional attention to detail., Ability to clearly communicate consumer data issues to both technical and business stakeholders.
Nice to Have
Experience testing analytics in Tableau, ThoughtSpot, Looker, or similar BI platforms., Familiarity with consumer identity, event tracking, and behavioral data models., Exposure to data quality frameworks, reconciliation processes, or automated data validation., Experience with CI/CD pipelines and version control (e. g. , Git) in analytics environments., Understanding of consumer data governance, lineage, and metadata practices., Knowledge of privacy and compliance considerations related to consumer data (GDPR, CCPA)., Experience with automation tools such as Postman, Pytest, or SQL-based testing frameworks.
What You'll Do.
Validate consumer identity
and transactional data across all layers of the data platform.
Perform end-to-end dataset comparisons.
Reconcile consumer metrics and KPIs displayed in dashboards against upstream source and warehouse tables.
Test ETL/ELT pipelines that ingest and transform consumer data.
Validate business logic related to consumer attribution
and aggregation rules.
and trend-based testing.
Create reusable test plans
validation checklists
and reconciliation queries.
How You'll Work.
Team & Collaboration
Partner with data engineers and analytics teams to investigate and resolve consumer data quality issues.; Participate in Agile ceremonies, including sprint planning, backlog refinement, and retrospectives.; Collaborate to find new and better ways to create innovative products and experiences.; Work closely together to achieve shared values and common goals.
Communication Scope
Ability to clearly communicate consumer data issues to both technical and business stakeholders.
Process & Methodology
Agile ceremonies, sprint planning, backlog refinement, retrospectives
Full Job Description
CREATIVITY IS OUR SUPERPOWER. It’s our heritage and it’s also our future. Because we don’t just make toys. We create innovative products and experiences that inspire fans, entertain audiences and develop children through play. Mattel is at its best when every member of our team feels respected, included, and heard—when everyone can show up as themselves and do their best work every day. We value and share an infinite range of ideas and voices that evolve and broaden our perspectives with a reach that extends into all our brands, partners, and suppliers. The Team: The Opportunity: Key Responsibilities * Validate consumer identity, profile, behavioral, and transactional data across all layers of the data platform, from source systems through curated analytics datasets. * Perform end-to-end dataset comparisons to ensure consumer-level records, counts, and attributes remain consistent as data moves through ingestion and transformation layers. * Reconcile consumer metrics and KPIs displayed in Tableau and ThoughtSpot dashboards against upstream source and warehouse tables. * Test ETL/ELT pipelines that ingest and transform consumer data, including events, purchases, interactions, and engagement signals. * Validate business logic related to consumer attribution, segmentation, and aggregation rules used in analytics. * Conduct row-level, aggregate-level, and trend-based testing to identify issues such as duplication, data loss, mis-joins, or incorrect consumer rollups. * Partner with data engineers and analytics teams to investigate and resolve consumer data quality issues. * Create reusable test plans, validation checklists, and reconciliation queries for consumer analytics datasets. * Document test cases, validation results, and QA approvals for consumer data releases. * Participate in Agile ceremonies, including sprint planning, backlog refinement, and retrospectives. * Contribute to the continuous improvement of consumer data QA standards, validation frameworks, and au
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