Test Engineer

Position Overview

The Test Engineer will own hands-on quality engineering for the AWS Policy Master flow, with primary emphasis on automated data, API, integration, reconciliation, resilience, performance, and production-readiness testing. The role validates that policy feeds are accurately processed from S3 through Lambda and SQS into Aurora and are securely exposed through APIs. The engineer will collaborate closely with developers and business SMEs to build traceable test coverage, detect defects early, validate nonfunctional requirements, and provide objective release-readiness evidence.

Required Skills and Experience

• 57 years of software testing or quality-engineering experience, including substantial automation experience on cloud, data, API, integration, or distributed-system programs.
• Hands-on experience testing AWS-based solutions using services such as S3, Lambda, SQS, EventBridge, Aurora PostgreSQL, API Gateway, CloudWatch, IAM, and KMS.
• Strong skills in SQL and data validation, including source-to-target reconciliation, transformation-rule testing, referential integrity, duplicates, nulls, control totals, historical or effective-dated data, and exception validation.
• Experience building automated test frameworks using Python, Java, or JavaScript and tools such as pytest, JUnit, REST Assured, Postman/Newman, Karate, or equivalent.
• Experience with REST API testing covering contracts, schemas, authentication and authorization, pagination, versioning, throttling, negative scenarios, error responses, and performance.
• Practical experience testing asynchronous and event-driven patterns, including message sequencing, duplicate delivery, idempotency, retry, dead-letter queues, replay, partial failure, and eventual consistency.
• Experience with performance and reliability tools such as JMeter, Gatling, k6, or equivalent, plus observability through CloudWatch logs, metrics, dashboards, and alerts.
• Working knowledge of CI/CD quality gates, Git workflows, defect management, test-data management, environment readiness, and traceability from requirements to test evidence.
• Strong analytical and communication skills, with the ability to isolate defects across application, data, infrastructure, and integration layers and communicate business impact clearly.
• Insurance policy-domain knowledge, testing of policy administration or ODS solutions, and familiarity with PII or regulated-data controls are preferred; ISTQB or an AWS certification is an advantage.

Duties

• Translate business, data, API, security, and nonfunctional requirements into a risk-based test strategy, detailed scenarios, automation scope, and entry or exit criteria.
• Develop and execute automated tests across S3 landing, Lambda validation, SQS buffering, transformation processing, Aurora persistence, and API consumption.
• Validate source-to-target mappings and canonical policy rules through record-level comparison, aggregate reconciliation, control totals, exception reporting, and negative-data scenarios.
• Test asynchronous behavior including duplicate messages, out-of-order events, poison messages, retries, dead-letter queues, replay, timeout, partial failure, and recovery without data loss or corruption.
• Automate API functional, contract, authorization, error-handling, throttling, versioning, and regression tests and integrate them into CI/CD pipelines.
• Execute performance, load, volume, endurance, concurrency, and resilience testing against agreed service levels; identify bottlenecks across Lambda, queues, Aurora, and APIs.
• Validate security controls including least-privilege access, encryption, secrets handling, sensitive-data masking, audit events, and unauthorized-access behavior in partnership with security teams.
• Create representative and privacy-compliant test data, manage test-data refreshes, and maintain reusable automated datasets and expected-results libraries.
• Log high-quality defects with evidence, severity, reproducibility, impacted data or services, and likely failure layer; support triage, root-cause isolation, retesting, and closure.
• Track coverage, automation rate, pass or fail trends, defect leakage, reconciliation results, performance findings, and residual risk; provide an evidence-based release recommendation.
• Support production-readiness validation, cutover rehearsals, smoke testing, hypercare, incident reproduction, and continuous improvement of the regression suite.