Description

Key Skills: SQL, Data Validation, ETL Testing, BigQuery, JIRA, Data Pipelines, Analytics, Consumer Data, Quality Assurance, Data Quality

Good to Have Skills: Experience with 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 (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.

Roles & 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 automation coverage.

Experience Required: 2–5 years of QA experience focused on consumer data, analytics, or business intelligence. Strong proficiency in SQL for validating consumer-level datasets. Hands-on experience testing data pipelines within modern data lake or warehouse architectures. Proven experience validating consumer-focused dashboards and metrics in BI tools

Key Skills

Education

Any Graduate