Austin; New York City; United StatesNot specifiedSenior
Salary not listed
AWS
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Austin; New York City; United States
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About the role
Join the MongoDB Server Query Optimization team, and help us build a world-class distributed open-source query optimizer. Our team plays a crucial role in the experience and performance of data processing. We are responsible for the MongoDB Query Language and the lifecycle of each query, through parsing, optimization and plan selection.
We have tons of interesting problems to solve with a direct impact on users for transactional, time-series, and analytical workloads. The team is endeavoring to systematically rewrite every major component of our optimization and execution systems. We need your help to design and build the heart of a distributed, flexible schema, document database.
This role can be based remotely in the U.S. or Canada, limited to Eastern or Central time zones only.
CANDIDATE PROFILE
5+ years of experience in data management systems, distributed systems, or large-scale backend engineering
Experience with building production-level code with a large user base, robust design structure and rigorous code quality
Degree in Computer Science or similar field, or equivalent practical experience, with strong competencies in data structures, algorithms, and software design/architecture
Experience with large code bases written in C++ or another systems programming language. You'll need to trace down defects, estimate work complexity, and design evolution and integration strategies as we rewrite different components of the system
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
A strong foundation in core database internals is essential. While direct experience in query optimization is a massive bonus, it is not a prerequisite. We are also excited to meet candidates with strong backgrounds in compilers, language transpilers, or distributed storage systems
POSITION EXPECTATIONS
Innovate in the area of flexible schema databases. Help us build a world-class query optimization system
Research state-of-the art query systems to inform our design
Leverage deep knowledge of the strength and weakness of the product and of industry trends to provide technical vision and direction
Set initiative level strategy, architect plans, and lead the team towards successful execution
Advise and partner with management on roadmap decisions, processes, and architectural designs
Identify, design, implement, test, and support new features related to query performance and robustness, query language enhancements, diagnostics, and integration with other products and tools
Work with other engineers to coordinate seamless changes in a feature-rich, large code base
Work with other teams including client drivers, cloud services, enterprise tools, support, consulting, education, and marketing to coordinate changes or contribute to their projects
Influence and grow team members through active mentoring, coaching and leading by example
SUCCESS MEASURES
In three months you’ll have contributed to the development of a project slated for the next major version, as well as fixed a few bugs in a minor version of our latest stable release series; You'll have learned about MongoDB's project lifecycle, and our long-term goals for the system
In six months, you’ll have taken on code review responsibilities and are playing an active role in drafting and reviewing the design for new features; You have expanded the team's horizons by presenting a favorite paper or system architecture related to query systems
In twelve months, on the basis of your extensive past experience in the query space, you have contributed to the long-term technical roadmap of the MongoDB Query team
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 data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely available, globally distributed data platform 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 data platform and is available across AWS, Google Cloud, and Microsoft Azure.
With offices worldwide and over 67,000 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, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Req. ID: 1273425622
MongoDB’s base salary range for this role is posted below. Compensation at the time of offer is unique to each candidate and based on a variety of factors such as skill set, experience, qualifications, and work location. Salary is one part of MongoDB’s total compensation and benefits package. Other benefits for eligible employees may include: equity, participation in the employee stock purchase program, flexible paid time off, 20 weeks fully-paid gender-neutral parental leave, fertility and adoption assistance, 401(k) plan, mental health counseling, access to transgender-inclusive health insurance coverage, and health benefits offerings. Please note, the base salary range listed below and the benefits in this paragraph are only applicable to U.S.-based candidates.
MongoDB’s base salary range for this role in the U.S. is: $126,000—$248,000 USD
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operati