Senior Quality Test Engineer I
hace 1 semana
About the Business:
LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertically, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below,
About our Team:
This group is collaborative and supportive, with members committed to each other's growth. Successful teams here are quick learners who adapt, deliver value, and work well together.
You will design automation strategies for critical applications and data infrastructure, support adoption of AI tools for engineering productivity, and help engineers build, monitor, and maintain high-quality products for clinical data use cases.
About the Role:
A senior QA & automation engineer is needed to direct quality assurance activities for the enterprise data lake platform. This position involves developing thorough testing protocols, possessing substantial knowledge in both general and data quality validation, and utilizing AI tools to enhance engineering effectiveness for the team.
Responsibilities:
Test Automation & Integration: architect and maintain end-to-end testing frameworks to support a variety of engineers working across various services (APIs, UI/UX, data pipelines, serverless applications).
Testing Protocol Establishment: define and inform best practices on maintaining quality metrics across our data and application platforms.
Data Quality and Validation: design and implement frameworks to help profile, monitor, proactively detect issues with critical data products.
AI-leveraged Engineering: leverage LLMs to accelerate tasks like test case generation, document creation, code review, synthetic/test data generation.
Requirements:
- 5+ years in quality focused automation engineering, with a strong understanding of how to set a high bar for quality for complex applications and data systems
- Self-starter and ability to drive impact with minimal high-level direction
- Strong programming skills in Python or , and CI/CD tools
- Experience building internal tools, automation scripts, and operational dashboards.
- Solid understanding of microservices, APIs, and backend architecture principles to design and develop effective internal tools and operational workflows.
- Experience with distributed systems and cloud computing (AWS, Azure, GCP)
- Has worked with data-intensive systems (distributed datastores, data warehouses/lakes, big data processing)
Preferred Qualifications
- Experience with HIPAA or other compliance-heavy industries
- Experience with infrastructure as code (Terraform, Cloudformation)
- Background in data and analytics
Technical Skills:
- Programming: Python, , SQL
- Data Technologies: Apache Spark, Kafka, Delta Lake, Databricks, Looker
- Cloud Platforms: AWS, Azure, GCP
- Testing Tools: Playwright, pytest, Jest, great expectations or similar tools.
- Automation: Jenkins, Gitlab CI, Github Actions, Apache Airflow
- Monitoring: Datadog, Prometheus, Cloudwatch
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