Senior Quality Assurance Engineer

ZipRecruiter
London
6 days ago
Create job alert

Job Description

About KX:

Our mission is to accelerate data and AI-driven innovation with high performance analytics solutions, enabling our customers to transform into AI-first enterprises. KX is trusted by the world's top investment banks & hedge funds, aerospace and defence, life and health sciences, semiconductor, telecommunications, and advanced manufacturing companies.

Time series and vector data analytics and management are at the heart of our products, independently benchmarked as the fastest on the market. They help our customers process data at unmatched speed and scale and empower LOB leaders, developers, data scientists, and data engineers to build high-performance data-driven applications and turbocharge their favourite analytics tools in the cloud, on premise, or at the edge.

KX technology enables the discovery of richer, actionable insights for faster, better-informed decision making which drives competitive advantage and transformative growth for our customers. KX operates across North America, Europe, and Asia Pacific.

Role Overview:

We are seeking a highly skilled Senior QA Engineer to join our growing team and ensure the quality and reliability of our software solutions. The ideal candidate will have extensive experience in quality assurance of large-scale Enterprise Software products involving full software development lifecycle - starting from validation of user needs & software requirements to delivery of features and gathering feedback from end users.

As a Senior QA Engineer at KX, you will be responsible for leading the quality assurance efforts for our software products. You will design and implement testing strategies, automate test cases, and work closely with development teams to identify and resolve issues. Your expertise will help us maintain high standards of quality and deliver exceptional products to our customers.

Your responsibilities will include helping the team deliver good quality responsive web applications with speed & efficiency, testing quality of features, defect reporting, helping the team with troubleshooting & debugging defects, contributing towards internal technical documentation, and liaising with support representatives to solve customer issues.

Key Responsibilities:

  • Test Strategy: Develop and implement comprehensive test strategies and plans to ensure the quality of software products. Testing of both functional and non-functional elements of the product features.
  • Automation: Design, develop, and maintain automated test scripts using tools such as Cypress, Selenium, JUnit, or similar frameworks.
  • API Testing: Implement API Testing strategies, standards & tooling.
  • Manual Testing: Perform manual testing when necessary to validate functionality and identify defects.
  • Test Case Management: Create, maintain, and execute detailed test cases and test scenarios.
  • Defect Tracking: Identify, document, and track defects using bug tracking tools like JIRA or Bugzilla.
  • Collaboration: Work closely with development, product management, and other cross-functional teams to ensure quality throughout the software development lifecycle. Participate in code reviews and provide feedback on testability.
  • Performance Testing: Conduct performance and load testing to ensure the software meets performance requirements.
  • Regression Testing: Perform regression testing to ensure existing functionality is not affected by new changes.
  • Continuous Improvement: Continuously improve testing processes and methodologies to enhance efficiency and effectiveness.
  • Mentorship: Provide guidance and mentorship to junior QA engineers, fostering a collaborative and growth-oriented environment.
  • Reporting: Report and track defects, and work with developers to resolve them, generate & present detailed test reports and metrics to stakeholders.

Key Skills and Qualifications:

  • Qualifications: Bachelor's degree in computer science, Engineering, or a related field or equivalent experience.
  • Experience: 7+ years of proven experience as a QA Engineer, QA Lead or similar role.
  • Technical Expertise: Strong knowledge of QA methodologies, tools, and processes.
  • Automation Skills: Proficiency in test automation tools and frameworks (e.g., Selenium, JUnit, TestNG).
  • Programming: Basic understanding of programming such as Python or JavaScript.
  • Manual Testing: Experience in manual testing and creating detailed test cases.
  • Defect Tracking: Familiarity with defect tracking tools (e.g., JIRA, Bugzilla).
  • Performance Testing: Experience with performance and load testing tools (e.g., JMeter, LoadRunner).
  • Collaboration: Excellent collaboration skills and the ability to work effectively with cross-functional teams.
  • Problem-Solving: Excellent problem-solving skills, ability to identify, analyse, and resolve issues effectively.
  • Agile Methodologies: Familiarity with agile development processes and working in sprints.
  • Communication & Soft Skills: Strong verbal and written communication skills, strong interpersonal skills, highly motivated and self-directed, capable of multi-tasking, and able to work with minimal supervision, exceptional attention to detail.

Required Tools and Technologies:

  • Test Suite: Demonstrable ability to manage & maintain Test Suites in a test management software.
  • Frameworks: Test automation scripting - Selenium / Cypress, basic knowledge of JavaScript/Typescript.
  • API Testing: API Testing strategies, standards & tooling - REST/GraphQL/gRPC, Open API v3, cURL, PostMan.
  • Version Control: Good understanding of Version control - Git.
  • Agile Tooling: JIRA, Confluence.
  • Development Tools: VS Code, Basic Scripting - Bash, PowerShell.

What would help:

  • Frameworks: Basic knowledge of Python, JavaScript/Typescript, HTML5/CSS, Responsive UI design.
  • Containerization: Some exposure to containerization technologies (e.g., Docker, Kubernetes).
  • Cloud Platforms: Basic familiarity with cloud platforms - AWS / Azure / GCP.
  • CI/CD Tools: Some exposure to CI/CD tooling such as GitLab CI, GitHub Actions.
  • DevOps, DevSecOps: Basic understanding of DevOps & DevSecOps best practices.
  • Security & Privacy: Good understanding of security testing strategies, chaos & performance testing, security benchmarks (Pen Testing, CIS/NIST etc) and privacy legislations (GDPR).
  • Development Tools: Some experience with VS Code, Basic Scripting - Bash, PowerShell.
  • Databases: Basic understanding of SQL/NoSQL databases (PostgreSQL, MongoDB, Redis) and their testing.

Location & Workplace Type:

This position takes on a hybrid working model based in London.

Why Choose KX?

Data Driven:We lead with instinct and follow fact.

Naturally Curious:We lean in, listen and learn fast.

All In:We take ownership, take on challenges and give it our all.

#J-18808-Ljbffr

Related Jobs

View all jobs

Senior QA Officer

Senior Quality Assurance Analyst

Senior Data and Analytics Manager

Senior Data Services Manager

Senior Data Services Manager

Azure Data Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

10 Essential Books to Read to Nail Your Data Science Career in the UK

Data science continues to be one of the most exciting and rapidly evolving fields in tech. With industries across the UK—ranging from finance and healthcare to e-commerce and government—embracing data-driven decision-making, the demand for skilled data scientists has soared. Whether you're a recent graduate looking for your first role or a professional aiming to advance your career, staying updated through books is crucial. In this article, we explore ten essential books every data science job seeker in the UK should read. Each book provides valuable insights into core concepts, practical applications, and industry-standard tools, helping you build skills employers are actively looking for.

Navigating Data Science Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Data science has taken centre stage in the modern workplace. Organisations rely on data-driven insights to shape everything from product innovation and customer experience to operational efficiency and strategic planning. As a result, there is a growing need for skilled data scientists who can analyse large volumes of data, build predictive models, communicate findings effectively, and collaborate cross-functionally. If you are looking to accelerate your data science career—or even land your first role—attending data science career fairs can be a game-changer. Unlike traditional online applications, face-to-face interactions let you showcase your personality, passion, and communication skills in addition to your technical expertise. However, to stand out in a busy environment, you need a clear strategy: from polishing your personal pitch and asking thoughtful questions to following up with a memorable message. In this article, we’ll guide you through every step of making a strong impression at data science career fairs in the UK and beyond.

Common Pitfalls Data Science Job Seekers Face and How to Avoid Them

Data science has become a linchpin for decision-making and innovation across countless industries, from finance and healthcare to tech and retail. The demand for data scientists in the UK continues to climb, with businesses seeking professionals who can interpret complex datasets, build predictive models, and communicate actionable insights. Despite this high demand, the job market can be extremely competitive—and many applicants unknowingly fall into avoidable traps. Whether you’re an aspiring data scientist fresh out of university, a professional transitioning from a quantitative role, or a seasoned analyst looking to expand your skill set, it’s crucial to navigate your job search effectively. In this article, we explore the most common pitfalls data science job seekers face and provide pragmatic advice to help you stand out. By refining your CV, portfolio, interview strategies, and communication skills, you can significantly increase your chances of landing a rewarding data science role. If you’re looking for your next data science job in the UK, don’t forget to explore the listings at Data Science Jobs. Read on to discover how to avoid critical mistakes and position yourself for success.