Data QA Automation

About the Role

We are looking for a Data QA Automation with strong experience in data validation, automation, analytics testing, and large-scale event pipeline quality.

This role is focused on ensuring the accuracy, stability, and reliability of data across our analytics and security event systems. The ideal candidate will be responsible for building automated validations, investigating data discrepancies, monitoring data quality, and working closely with engineering, data, and product teams.

Responsibilities

Design, build, and maintain automated validation processes for large-scale event pipelines.

Validate end-to-end data flows across ingestion, processing, storage, and dashboard layers.

Create SQL-based validations to verify event counts, unique devices, metadata accuracy, schema

consistency, latency, and data freshness.

Investigate discrepancies between production systems, staging environments, data warehouses, object

storage, and customer-facing dashboards.

Monitor event volume, data latency, anomalies, spikes, drops, duplicates, and missing data.

Build and maintain CI/CD validation jobs using tools such as Jenkins or GitLab CI.

Create clear automated reports, dashboards, and email summaries for validation results.

Work closely with backend engineers, data engineers, QA teams, and product stakeholders to identify,

report, and validate fixes for data quality issues.

Support performance and scalability testing for analytics dashboards, queries, and data pipelines.

Help improve internal data assurance processes, data observability, and production monitoring.

Requirements

2+ years of experience in Data Assurance, Data Validation, QA Engineering, or a similar role.

Strong hands-on experience with SQL and data validation.