QA engineer(AWS+Kafka+Datapipelines+Widsurf

ob Description: Senior Quality Analyst (Kafka Pipeline, AWS setup, Data Pipelines, Python, Payment integrity)

Location: Saint Lois, MO/ Dallas / New York (hybrid)

C2C or W2

Experience- 7+ Years

We are seeking an experienced Senior Quality Analyst to support the project initiative. The ideal candidate will have strong experience testing cloud-native, configuration-driven, event-based, and data-processing platforms.

This role requires hands-on expertise in Python-based test automation, AWS services, Kafka, data pipeline validation, API testing, database testing, CI/CD, containerization, observability, and production-quality engineering.

Experience

• 7+ years of overall experience in software quality engineering or software engineering.
• 5+ years of hands-on experience testing AWS-based applications, Kafka integrations, and data pipelines.
• Demonstrated experience designing and implementing automated testing frameworks using Python.

Key Responsibilities

• Develop and execute comprehensive test strategies for the PISCES HUB platform.
• Design and maintain Python-based automation frameworks for API, integration, data pipeline, and end-to-end testing.
• Validate AWS-based data pipelines, event-driven workflows, and distributed application components.
• Test Kafka producers, consumers, topics, partitions, schemas, offsets, retries, and failure-recovery scenarios.
• Validate data accuracy, completeness, consistency, transformation logic, lineage, and reconciliation across pipelines.
• Test configuration-driven solutions, including metadata-driven workflows, dynamic business rules, and configurable integration frameworks.
• Validate JSON-, YAML-, and XML-based configurations, including schema validation, version compatibility, error handling, and backward compatibility.
• Perform functional, integration, regression, system, and negative testing.
• Validate REST APIs, asynchronous services, batch processes, and event-based integrations.
• Test SQL and NoSQL databases for data integrity, rule-configuration storage, versioning, auditability, and rollback capabilities.
• Integrate automated test suites with CI/CD pipelines and GitOps workflows.
• Test containerized workloads deployed using Docker, Kubernetes, Amazon EKS, and Amazon ECS.
• Use Dynatrace to monitor application behavior, analyze logs and traces, identify performance bottlenecks, and support root-cause analysis.
• Collaborate with developers, architects, product owners, DevOps engineers, and data engineers to define acceptance criteria and improve overall product quality.
• Track defects through resolution and provide clear reporting on testing progress, quality risks, and release readiness.
• Use Windsurf and other AI-assisted engineering tools to accelerate test-case creation, automation development, troubleshooting, and documentation.

Required Technical Skills

• Strong proficiency in Python, including the development of reusable automation frameworks and test utilities.
• Hands-on experience with Python testing tools such as Pytest, unittest, requests, or equivalent frameworks.
• Strong experience testing AWS data pipelines and cloud-native applications.
• Hands-on knowledge of the following AWS services:
• Amazon EKS
• AWS Lambda
• Amazon ECS
• Amazon S3
• Amazon RDS
• Amazon DynamoDB
• Strong experience testing Apache Kafka-based event-driven architectures.
• Proven experience validating:
• Metadata-driven pipelines and workflows
• Dynamic business-rule engines
• Configuration-driven applications
• Configurable APIs and data-integration frameworks
• Experience testing JSON-, YAML-, and XML-based configuration interpreters.
• Strong SQL skills and experience validating relational and NoSQL data stores.
• Understanding of database models used to store, version, audit, and retrieve rule configurations.
• Experience with API testing tools and frameworks such as Postman, REST Assured, or Python Requests.
• Strong understanding of CI/CD pipelines, Git, and GitOps practices.
• Hands-on experience with Docker, Kubernetes, and containerized application testing.
• Strong working knowledge of Dynatrace for monitoring, observability, performance analysis, and troubleshooting.
• Working knowledge of Windsurf or similar AI-assisted development tools.

Preferred Qualifications

• Experience testing high-volume, distributed, event-driven platforms.
• Experience with data reconciliation, schema evolution, data-contract testing, and data-quality validation.
• Familiarity with Kafka schema management and serialization formats such as Avro, JSON, or Protobuf.
• Experience with performance-testing tools such as JMeter, Locust, or Gatling.
• Familiarity with infrastructure-as-code and deployment tools such as Terraform, Helm, or Argo CD.
• AWS or software-testing certifications are an advantage.

Key Competencies

• Strong analytical and problem-solving abilities.
• Quality-first mindset with strong attention to detail.
• Ability to understand complex data flows and distributed system architectures.
• Strong debugging and root-cause-analysis skills.
• Ability to work independently and collaborate across engineering teams.
• Clear written and verbal communication skills.
• Ability to identify quality risks and communicate release-readiness recommendations to stakeholders.