招聘
福利待遇
•Parental Leave
必备技能
Test Automation
Programming
Data Structures
Algorithms
Software Design
The MongoDB Query Team is hiring Software Engineers who want to join us in building a state-of-the-art distributed query system. We are responsible for the MongoDB Query Language and the lifecycle of each query, from parsing to optimization to plan selection; our engineers work on maintaining and improving our optimization and execution frameworks and building new query language features to help power our customers' critical workloads. Throughout all our work, our highest priority is always ensuring that customer queries are answered correctly. The successful applicant will be responsible for helping us to maintain the highest standards of quality through rigorous testing and automation strategies.
We are looking to speak to candidates who are based in Dublin for our hybrid working model.
Candidate Profile
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Minimum 5 years of experience in QA automation or software development with a focus on test automation
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Significant programming experience
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Ability to work in highly ambiguous environments
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Proficiency in writing and maintaining test automation for large codebases
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Experience with testing multi-tiered backend systems
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Solid foundation in computer science, with knowledge of data structures, algorithms, and software design/architecture
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Passion for quality and an understanding of the latest test automation technologies and frameworks
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Experience in developing performance test plans and monitoring frameworks
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Experience in distributed query processing engines performance testing is a plus
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B.Sc. in Computer Science or related field, or equivalent practical experience. Advanced degrees of experience in database query engines is a plus
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Background in databases, data management systems, and understanding of database query engines is a strong plus
Position Expectations
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Design, develop, and maintain correctness and performance automated tests and testing frameworks for the MongoDB query engine
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Collaborate closely with peers to understand new features and functionalities, ensuring testability and coverage for automating tests of both happy-path and edge-case scenarios
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Identify, isolate, and document bugs and issues within the database query system. Work with developers to ensure issues are resolved
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Enhance and extend the automation framework to improve test coverage, execution time, and tooling for diagnostics and performance testing
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Review and approve testing plans drawn up in the design phase of Query team projects. At the end of the project, certify that it has met its commitments regarding test coverage
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Provide feedback in code reviews, focusing on the robustness and reliability of code changes from a testing perspective
Success Measures
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Within three months, you have gained an understanding of MongoDB's MQL syntax and its semantics, as well as the behavior of our unique query engine and its interaction with other server systems (storage/indexes, sharding, etc). You are able to contribute effectively for testing improvements in correctness and performance testing
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By six months, you have established yourself as a reviewer for automated tests, independently leading the testing efforts for complex functionalities, and demonstrating improvements in test efficiency and coverage. You have contributed to increasing the automated test coverage for upcoming releases
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After twelve months, you are a solid contributor to testing strategy for new features, supporting new team members in best practices for test automation, performance testing and quality assurance
About MongoDB
MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.
With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.
Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.
To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!
MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.
MongoDB is an equal opportunities employer.
REQ ID:4263348258
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关于MongoDB

MongoDB
PublicMongoDB, Inc. is an American software company that develops and provides commercial support for the source-available database engine MongoDB, a database for unstructured data.
5,000+
员工数
New York
总部位置
$24.0B
企业估值
评价
2.6
10条评价
工作生活平衡
3.2
薪酬
3.8
企业文化
2.8
职业发展
2.9
管理层
2.4
35%
推荐给朋友
优点
Great team environment and culture
Supportive management and mentorship
Good compensation and benefits
缺点
Poor leadership and decision-making
Declining sales culture and difficult quotas
Limited advancement opportunities
薪资范围
30个数据点
Mid/L4
Senior/L5
Mid/L4 · Manager Marketing Analytics and Operations
1份报告
$114,266
年薪总额
基本工资
$99,362
股票
-
奖金
-
$114,266
$114,266
面试经验
8次面试
难度
3.1
/ 5
时长
14-28周
体验
正面 0%
中性 88%
负面 12%
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Final Round
常见问题
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
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