Senior QA Engineer(GCP)

Senior QA Engineer (GCP)

Key Requirement: 4+ years of hands-on experience testing solutions on Google Cloud Platform (GCP) — this is non-negotiable.

Role Summary

We are seeking a hands-on QA Engineer or QA Analyst to validate the  GCP ingestion framework developed with Java, microservices, Google Cloud Platform (GCP), and Kubernetes. The successful candidate will define and execute a comprehensive quality strategy for enterprise data ingestion and downstream processing.

This role will analyze the frameworks built, create traceable test coverage, and validate full loads, incremental loads, and partition-overwrite loads. The candidate will test framework reliability, data accuracy, error handling, alerting, and operational readiness, then provide evidence for signoff and support promotion through SIT, PRE-PROD, and PROD environments.

Key Responsibilities

1. Quality Strategy & Test Design

• Collaborate with product and engineering to translate requirements into testable, risk-based strategies.
• Design comprehensive test plans, scenarios, and traceability matrices — from early design to release.
• Define clear entry/exit criteria, test data needs, and signoff evidence — ensuring quality is measurable and auditable.

2. Functional & Data Validation

• Validate end-to-end data ingestion: full, incremental, and partition-overwrite loads — including watermarking, deduplication, and restartability.
• Reconcile source and target data: counts, schemas, business keys, and field-level accuracy.
• Test edge cases: malformed records, nulls, duplicates, empty inputs, large files, and boundary conditions.

3. Automation & CI/CD Integration

• Build and maintain automated test suites (API, integration, data validation, regression, smoke) for Java/microservice systems.
• Integrate tests into CI/CD pipelines — publishing clear, actionable results and evidence.
• Manage reusable test data, mocks, stubs, and environment-agnostic setups for consistent, repeatable testing.

4. Resilience, Observability & Non-Functional Testing

• Test error handling, retries, idempotency, dead-letter handling, and recovery workflows.
• Validate Cloud Monitoring, logging, alerting, and dashboard reliability.
• Conduct performance, scalability, concurrency, soak, and recovery testing — especially for high-volume ingestion.
• Assess Kubernetes health (readiness/liveness probes, scaling, restart behavior) and cloud-native deployments.
• Verify security controls: IAM, secrets management, least-privilege access, and data protection.

5. Defect Management & Release Readiness

• Log clear, reproducible defects with business impact, logs, and evidence — and partner with teams to resolve them.
• Lead regression cycles, manage defect aging, and support release-readiness reviews.
• Produce test completion reports, quality dashboards, and formal signoff packages for SIT, PRE-PROD, and PROD.

Required Qualifications

• 4+ years of hands-on QA experience — especially with enterprise data platforms, APIs, or ingestion systems.
• Proven ability to design and execute test strategies, plans, and traceability matrices.
• Experience testing Java apps, REST APIs, microservices, batch/streaming pipelines, and distributed systems.
• Strong GCP experience: Cloud Storage, BigQuery, Pub/Sub, Dataflow, Cloud Monitoring, etc.
• Deep familiarity with full-load, incremental-load, partition-overwrite, watermarking, reconciliation, and idempotency scenarios.
• Advanced SQL and data-validation skills: source-to-target checks, schema validation, control totals.
• Automation experience: CI/CD integration, test frameworks (Java-based), and test reporting tools.
• Comfort with Kubernetes/containerized apps: health checks, config, scaling, and deployment behavior.
• Ability to analyze legacy behavior, clarify ambiguous requirements, and communicate quality risks to stakeholders.
• Experience supporting testing across SIT, PRE-PROD, and PROD environments.

Preferred Qualifications

• Experience with ATLAS or similar enterprise ingestion frameworks (or legacy modernization projects).
• Hands-on with Docker, Kubernetes, Helm, Terraform, and cloud-native CI/CD pipelines.
• Familiarity with Apache Beam, data pipelines, schema evolution, and data-quality controls.
• Ability to build quality dashboards, validate alerts, and produce incident-response evidence.
• Performance testing experience: large-volume loads, recovery, and production-readiness reviews.
• Background in Agile teams: estimation, backlog refinement, and cross-functional collaboration.
• Knowledge of cloud security best practices: IAM, secrets, network boundaries, and least-privilege validation.

Ready to help shape the future of enterprise data? We’d love to hear from you.