QA Engineer — Data & BI

Company: Sourcing Connect Consulting
Experience: 4–8 Years
Location: India — Remote
Shift: 1:30 PM – 11:30 PM IST
Engagement: Contract
Start Date: Immediate
Duration: Immediate to December 2026 — Extendable

Role Summary

We are looking for a QA Engineer — Data & BI to own quality assurance across the Insights Hub platform, covering source extraction, transformation, transcription, privacy controls, data pipelines and BI dashboards.

This is a data-centric QA role, where the focus is ensuring that data, metrics and AI outputs are accurate and that sensitive information does not reach downstream stores or dashboards.

Key Responsibilities

• Define and own test strategy across ETL, AI/ML outputs, APIs and BI layers.
• Establish release entry and exit criteria.
• Build automated data-quality checks covering completeness, uniqueness, referential integrity, schema conformance, freshness and source reconciliation.
• Validate transformation logic across the relational model.
• Verify derived metrics against agreed business definitions.
• Test PII detection and redaction across transcript variations.
• Ensure sensitive information does not leak into downstream stores or dashboards.
• Validate transcription quality and AI outputs through sampling, accuracy benchmarking and regression tracking.
• Test vector ingestion and retrieval, including point counts, payload integrity, deterministic IDs and search relevance.
• Perform API testing covering authentication, error handling, pagination and rate-limit behaviour.
• Validate Tableau and Superset dashboards against source-of-truth queries.
• Test filters, drill-down behaviour, row-level security and browser rendering.
• Build and maintain automated regression suites integrated with CI/CD.
• Conduct performance and load testing against agreed SLAs.
• Manage defect lifecycle including logging, triage, prioritization, root-cause narrative and closure verification.
• Support client UAT and prepare test plans, traceability matrices and release-readiness reports.

Must-Have Skills

• Proven QA experience on data platforms or data warehouse projects, rather than solely application/UI testing.
• Strong SQL for independent data validation and reconciliation.
• Python for test automation using pytest or equivalent.
• Experience with data-quality frameworks such as Great Expectations, Soda or dbt tests.
• API testing experience using Postman, REST Assured or Python-based approaches.
• ETL and pipeline testing experience, including incremental-load and backfill scenarios.
• Experience with Jira, Zephyr, TestRail or similar test/defect-management tools.
• Strong written communication and ability to produce client-facing quality documentation.

Preferred / Nice to Have

• Experience testing BI dashboards, particularly Tableau or Superset.
• Exposure to AI/ML output testing, evaluation design, sampling and non-deterministic output handling.
• Familiarity with GCP, BigQuery and Cloud Composer.
• Experience validating data privacy and compliance controls.
• Performance testing experience using JMeter, Locust or k6.
• CI/CD integration experience with GitHub Actions, Jenkins or Cloud Build.
• Financial services domain experience.