Data QA Automation
Core
Ensuring the accuracy, stability, and reliability of data across analytics and security event systems by building automated validations and monitoring data quality.
Role type
Data QA Automation Engineer
Builds
Automated validation processes, CI/CD validation jobs, and data quality reports for large-scale event pipelines.
Domain
Cybersecurity / Mobile App Protection / Data Engineering
Deliverable
production ML models
Required skills
SQL, data validation, automation (JavaScript/Node.js, Python), event pipeline testing, API testing, database testing, object storage testing, data observability, CI/CD integration, analytical thinking
Preferred skills
ClickHouse, Athena, S3, Kafka, Metabase, Parquet validation, Playwright, security analytics, Docker, AWS services
Responsibilities
Design 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.