Senior Software Engineer, Competitive Benchmarking

Mongodb · Mexicosenior

En corto

▸Ingeniero de software senior enfocado en pruebas de rendimiento comparativo de MongoDB.
▸Diseñas cargas de trabajo reales, construyes herramientas internas en Python y analizas resultados para influir en decisiones de producto.
▸Destaca por trabajar en un equipo que define estándares de benchmarking con impacto directo en el posicionamiento del producto.

Strong written and verbal communication skills, especially when explaining technical findi

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¿Qué piden?

✓5+ años construyendo sistemas distribuidos o altamente concurrentes
✓Fundamentos sólidos en ingeniería de software y análisis de rendimiento
✓Experiencia práctica con MongoDB, MQL y tuning de rendimiento
✓Experiencia en pruebas de carga, estrés, latencia y escalabilidad
✓Habilidades sólidas en Python y capacidad para aprender nuevas tecnologías rápidamente
✓Experiencia con al menos una nube: AWS, Azure o GCP, incluyendo trade-offs operativos

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

PythonMongoDBMQLAWSAzureGCPPostgreSQLMySQLAuroraCassandra

¿A quién escribirle en Mongodb?

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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 • 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 • Bache

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