Quality Assurance (QA Engineer)

• 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 automation coverage. 

What We’re Looking For: 

Required Qualifications 

• 2–5 years of QA experience focused on consumer data, analytics, or business intelligence. 

• Strong 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. 

• Strong analytical and troubleshooting skills with exceptional attention to detail. 

• Ability to clearly communicate consumer data issues to both technical and business stakeholders. 

Preferred Qualifications 

• 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.Top of Form