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About the role
MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unlock AI.
We’re looking for a Software Engineer to join the PM Benchmarking team in Mexico City. This team designs and executes competitive performance testing that benchmarks MongoDB against alternative technologies, while also building the reusable tooling, frameworks, and engineering practices needed to scale that work over time.
This role is a strong fit for an engineer who wants meaningful hands-on coding time, enjoys performance analysis, and is motivated by turning ambiguous technical questions into clear plans, repeatable systems, and high-impact outputs. You will work across the full lifecycle of a benchmark initiative: design, code, run, analyze, and communicate findings. You will also help improve the internal tooling and engineering workflows that make this work faster, more reliable, and more useful across MongoDB.
We are looking to speak to candidates who are based in Mexico for our hybrid working model.
WHAT YOU’LL DO
Design performance and benchmarking workloads that reflect realistic customer or product scenarios
Build and improve production-quality internal tooling, test harnesses, automation, and reusable workload components
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
Write and maintain code primarily in Python, while adapting to adjacent tools and technologies as needed
Run benchmarks across cloud environments and database platforms, with attention to fairness, noise reduction, cost, and repeatability
Analyze latency, throughput, scalability, and infrastructure signals to identify bottlenecks and explain results clearly
Translate broad business or engineering questions into scoped technical plans, success criteria, and execution milestones
Partner closely with Engineering, Product, Sales, and other stakeholders to ensure testing work is relevant and actionable
Produce clear technical documents, reports, and summaries that connect findings to product decisions and field value
Help shape team standards for documentation, onboarding, prioritization, and benchmark execution as the team continues to mature
Mentor peers where appropriate and contribute to a collaborative, low-ego engineering culture
WHAT WE’RE LOOKING FOR
5+ years of experience building, debugging, and improving distributed and/or highly concurrent software systems
Strong software engineering fundamentals, including writing maintainable code, profiling performance, and debugging complex issues
Hands-on experience with MongoDB architecture, MongoDB Query Language (MQL), and MongoDB performance tuning
Hands-on experience with performance testing methodologies such as load, stress, latency, or scalability testing
Experience designing and implementing benchmarking or performance-validation workflows
Strong coding skills in Python or a similar language, plus the ability to learn new stacks quickly
Strong hands-on experience with at least one of the three major cloud providers used for this role, AWS, Azure or GCP, including the practical trade-offs involved in running reliable applications at scale
Strong hands-on experience with PostgreSQL, MySQL, Aurora, Cassandra, or other competing data platforms
Ability to reason about relational and document data models, distributed systems behavior, and infrastructure bottlenecks
Strong written and verbal communication skills, especially when explaining technical findings to different audiences
Ability to work with ambiguity, define structure where needed, and operate with a high degree of ownership and autonomy
Bachelor’s degree in Computer Science or a related field, or equivalent practical experience
NICE TO HAVE
Experience with CI/CD systems and integrating automated tests into engineering workflows
Experience creating reusable technical documentation, runbooks, or internal playbooks
SUCCESS IN THIS ROLE
In your first 30 days
Build a clear understanding of the team’s current workloads, tooling, roadmap, and stakeholder landscape
Complete onboarding and identify the main technical systems, docs, and knowledge gaps relevant to your work
Start contributing code, review feedback, and execution support on active benchmark efforts
In your first 90 days
Independently contribute to the design, coding, execution, and analysis of multiple benchmark initiatives
Improve at least one area of the team’s tooling, documentation, or execution workflow
Build strong working relationships with key cross-functional partners
In your first 6 months
Own meaningful benchmark or tooling work from scoping through delivery
Improve repeatability, clarity, or efficiency in how the team designs, runs, or reports on tests
Contribute to mentorship, documentation, or process improvements that increase team autonomy
In your first 12 months
Be a trusted technical contributor across benchmark design, tooling, and analysis
Influence how the team prioritizes and scales its work
Expand your scope through technical leadership, cross-functional collaboration, and deeper ownership of systems and processes
MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation, please inform your recruiter.
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 AI-native startups and approximately 75% of the Fortune 100, 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.
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
