דרושים Developer Advocate Data Modeling ב-Mongodb ב-ארהב

• Product Strategy and Ownership: Drive the complete lifecycle of the product, from defining vision and strategy to roadmap creation and execution; Align product direction with business priorities, IT architecture, and stakeholder needs; Define the "art of the possible," balancing quick wins with long-term improvements, and advocate for strategic innovation in data products
• Requirements Gathering and Use Case Definition: Partner closely with stakeholders, including analysts, engineers, and product managers, to collect and document detailed business requirements; Interview diverse personas to determine use cases, user stories, and actionable solutions, ensuring stakeholder pain points are accurately captured
• Stakeholder Collaboration and Advocacy: Serve as the voice of the user, gathering feedback and championing their needs; Develop and maintain strong partnerships across business units, engineering teams, and executive leadership. Provide clarity and transparency to the business on product progress, prioritization decisions, and roadblocks
• Agile Product Management: Lead and drive agile ceremonies, from backlog grooming to sprint planning and retrospectives; Collaborate closely with technical teams to ensure timely and high-quality product delivery; Balance addressing tech debt while driving innovation and new feature development in sprints
• Enablement and Long-Term Discoverability: Build user-friendly documentation and guides to drive product adoption and longevity; Communicate complex concepts in a manner easily understood across multiple audiences, ensuring discoverability and literacy of data products
• Performance and Market Analysis: Define measurable product outcomes and success metrics. Continuously analyze data signals to inform innovation, roadmap prioritization, and product delivery; Conduct market research to stay up-to-date with industry trends and guide strategic direction for products and the Internal Data Platform
• Product Marketing & Adoption: Announce product features and datasets through effective product marketing strategies and evangelization efforts, driving adoption across MongoDB teams; Re-launch features as needed to invigorate usage and showcase core capabilities
• Change Management: Partner with change management and training teams to promote adoption of features and capabilities; Communicate product changes effectively and track KPI metrics for success

• Experience: 5+ years of experience in product management, preferably in data products, or equivalent work experience with a proven ability to define product scope and collaborate with technical teams to deliver impactful solutions
• Strategic Thinking: Demonstrated ability to align product roadmaps with business priorities, operational needs, and technical feasibility. Skilled at making trade-off decisions between scope, resources, and timelines
• Stakeholder Empathy: Strong stakeholder-focused mindset, with a track record of understanding pain points, building partnerships, and translating insights into actionable requirements and solutions
• Technical Strength: Deep understanding of data engineering, analytics, and UX fundamentals. Experience working with analysts, data scientists, engineers, product managers, and operators, with the ability to step into their shoes and anticipate their needs
• Agility in Execution: Proficient in leading agile teams and ceremonies, managing technical dependencies, and driving continuous improvement of product processes and user experiences
• Effective Communication: Exceptional written and verbal communication skills, enabling collaboration across diverse company audiences, both technical and non-technical
• Growth Mindset: Adaptable, eager to take on challenges beyond the defined scope, highly organized, and detail-oriented to ensure thorough execution and delivery
• Outcome-focused Approach: Strong focus on measurable product outcomes and iterative improvement, with the ability to define and monitor success metrics
• Educational Background: B.Sc. in Computer Science or a related field preferred, or equivalent work experience in technology and product domains

• Data Analytics Expertise: Experience with BI, data engineering, or analytics tools; enjoys digging into data for insights, progress validation, and new opportunities
• Market Awareness: Keeps up-to-date with market trends in databases, data science, and software development, influencing product strategies accordingly
• User Enablement: Skilled in creating guides, documentation, and onboarding materials for stakeholders, driving long-term stakeholder productivity
• Evangelization Passion: Demonstrates enthusiasm for promoting, re-launching, and driving adoption of products, datasets, and features
• Metadata Management Knowledge: Understands the importance of metadata creation and documentation for long-term discoverability and literacy of data products

This role can be based out of any office or remotely in North America.

• Hands-on experience with Python (or related language) programming experience in industry
• Solid experience and knowledge of testing techniques focused on distributed systems
• A demonstrated expertise of solid UX-focused design of CLIs for scalability and maintainability
• An appetite for continuous learning and improvement
• A strong interest in developer productivity or related infrastructural-focused role
• A deep empathy and eagerness to understand and solve customer problems
• A proven track record of ownership, from synthesizing use cases through to delivering solutions
• Experience working with remote teams

• Software ecosystems that contain and routinely run a large number of tests, from unit-level through end-to-end
• Database (or other large system) integration testing frameworks
• Test fuzzing
• C++, Java, and/or Go
• Sanitizers and other static analysis tooling
• Kubernetes and Containerization
• Software Architecture and Design Principles

• Design and develop critical features to evolve our test frameworks and tools
• Identify and resolve bugs within our test frameworks and tools
• Reduce technical debt through iterative, quality of life improvements
• Meaningfully contribute to cohesive strategies to enable the development organization to build with confidence using the right tool for the job
• Eagerness to learn and grow in a fast-paced environment, including leveraging supportive mentors
• Show deep empathy towards other developers to understand their pain points and provide impactful solutions
• Onboard quickly and successfully into unfamiliar tools and systems
• Collaborate productively with colleagues at all stages of project lifecycle (ideation, requirements gathering, design, execution, and delivery)

• Within 1 month, you will have completed several small engineering tasks. You will also have a very high-level understanding of the developer experience for the Server and Cloud teams at MongoDB
• Within 3 months, you will have core contributions to at least one feature. You will have a good understanding of the team's mission and goals
• In 6 months you will be confident in the space to jump into investigations, support colleagues looking for help, and drive 1-2 projects from launch-to-land

• 6+ years of professional software engineer experience with a strong focus on fullstack development
• Proven ability to build scalable, performance optimized, modern web applications using MongoDB, Node.js, TypeScript/JavaScript, and React
• Hands-on experience with unit testing (Cypress, Jest, Playwright, etc.)
• Experience integrating CI/CD pipelines, monitoring tools, and cloud infrastructure (AWS/GCP/Azure)
• Hands-on experience leveraging Kubernetes, Helm, and modern infrastructure-as-code tools
• Solid understanding of API Integrations and other kinds of service discovery mechanisms to build/maintain a robust service catalog
• Experience working within distributed systems and have designed highly-scalable systems across various projects
• Demonstrate sound engineering practices like continuous delivery and automated testing
• You have impact through your communication skills and can successfully partner with different engineering teams across domains such as product developers, platforms engineers and SREs, etc
• Comfortable writing and reviewing technical design documents and specifications

• Hands-on experience working with Backstage (by Spotify), including platform extensions, portal management, and integrating various systems and tools to make them available to end users
• Deep understanding of the Backstage architecture, including plugin development, software catalog, scaffolder, and TechDocs
• Bonus points if you have experience in using and applying large language models; Experience with AI application development is a plus

Upon successfully passing the preliminary screenings, candidates will be invited to participate in live coding assessments, followed by a system design evaluation, to determine the alignment of their technical proficiencies with the requirements of the role.

• In 3 months, you've gained a deep understanding of the Developer Productivity team ecosystem and build and deployment workflows
• In 6 months, you are successfully contributing to our projects, including deploying code to production and taking on troubleshooting issues and resolving bugs
• In 9 months, you are successfully leading aspects of the technical architecture and enhancement of our tech stack, and technical roadmaps for the teams
• In 12 months, you are successfully contributing to mentoring and growing other team members

• Be proficient in a statically typed, compiled language (we primarily use Go)
• Have solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture
• Have a track record of shipping systems in a Cloud environment, with proficiency in Kubernetes
• Have familiarity with managing cloud compute resources, such as virtual machines (ideally AWS EC2)
• Have familiarity with working with databases (ideally managing a noSQL database)
• Have familiarity with identifying performance and reliability bottlenecks in an existing software system, as well as identifying solutions and reliable measurements for future monitoring
• Be a helpful and thoughtful communicator with other engineers and stakeholders

• Scale our continuous integration ecosystem as it supports the needs of a growing engineering organization
• Support project owners and R&D Productivity teams by introducing functionality and simplifying existing functionality to streamline the testing process
• Propose well-reasoned features and solutions by incorporating user feedback, metrics, and company and department objectives.
• Incorporate AI tooling to improve support and developer experience

• In three months, you’ll have understood the high-level architecture of Evergreen and made contributions to the performance and reliability of our systems as well as features impacting our customers. You will be able to answer questions concerning the performance and operations of systems you have most actively worked on. You will be in discussions about next steps for larger projects to carry out.
• In six months, you will have led or been a major contributor on one or more substantial projects. You will be subject matter expert across most of our systems, able to understand how they are and are not interdependent, and will be able to answer questions about how they perform and operate. You will have also identified smaller architectural and operational improvements, especially by using your perspective and experience from outside MongoDB.
• In twelve months, You will regularly be initiating and leading technical projects and operational changes that have a substantial impact on our ability to deliver a smooth debugging and testing experience for the developers that use our products at MongoDB. You will be a strong technical resource across all of our systems as well as adjoining systems, and will be able to provide guidance about technical and operational direction across both. You will be responsible for mentoring newer and more junior members of the team, especially around concepts related to scaling and reliability.

As a senior software engineer on the Atlas Data Federation (ADF) team, you’ll be trusted with high-impact, high-visibility work on a rapidly growing platform. You’ll have the opportunity to design and implement core components of our distributed query engine. Your work will directly improve the performance, memory efficiency, and reliability of our systems. In addition, you’ll play a key role in improving our distributed control plane, which manages infrastructure and workload routing across the system. You'll participate in on-call rotations, leading incident response and postmortem analysis. Collaboration is central to this role—you’ll partner closely with other MongoDB teams, including those working on drivers, the core server, and cloud services, to ensure seamless integration and a cohesive developer experience.

• 3+ years of experience working on database or storage internals, or building core components of data processing systems such as query execution engines, storage layers, workload optimization, or autonomous tuning
• Proficiency in systems programming with languages like Go, Java, C++, or Rust
• Hands-on experience building and operating distributed systems at scale
• Excellent verbal and written technical communication skills and desire to collaborate with colleagues, mentor fellow engineers and lead projects
• Bachelor’s or Master’s degree in Computer Science or a related field, or equivalent practical experience

• In 3 months, you’ll have contributed to a key project and fixed a few impactful bugs
• In 6 months, you’ll be reviewing code and involved in design discussions for new features
• In 12 months, you’ll lead a major initiative and mentor newer engineers on the team

As a senior software engineer on the Atlas Data Federation (ADF) team, you’ll be trusted with high-impact, high-visibility work on a rapidly growing platform. You’ll have the opportunity to design and implement core components of our distributed query engine. Your work will directly improve the performance, memory efficiency, and reliability of our systems. In addition, you’ll play a key role in improving our distributed control plane, which manages infrastructure and workload routing across the system. You'll participate in on-call rotations, leading incident response and postmortem analysis. Collaboration is central to this role—you’ll partner closely with other MongoDB teams, including those working on drivers, the core server, and cloud services, to ensure seamless integration and a cohesive developer experience.

• 3+ years of experience working on database or storage internals, or building core components of data processing systems such as query execution engines, storage layers, workload optimization, or autonomous tuning
• Proficiency in systems programming with languages like Go, Java, C++, or Rust
• Hands-on experience building and operating distributed systems at scale
• Excellent verbal and written technical communication skills and desire to collaborate with colleagues, mentor fellow engineers and lead projects
• Bachelor’s or Master’s degree in Computer Science or a related field, or equivalent practical experience

• In 3 months, you’ll have contributed to a key project and fixed a few impactful bugs
• In 6 months, you’ll be reviewing code and involved in design discussions for new features
• In 12 months, you’ll lead a major initiative and mentor newer engineers on the team

As a Staff Engineer on the Atlas Data Federation and Archiving team, you will lead the design, optimization, and scalability of our storage and federated query systems. This role focuses on high-performance distributed storage, data lifecycle management, and efficient data retrieval at scale.

This role can be based in New York City, Austin, San Francisco, Seattle, or remotely in the United States.

Storage & Data Processing Performance

• Architect and optimize large-scale storage solutions for federated data access, ensuring efficient retrieval, indexing, and query performance
• Optimize data archival pipelines for high-throughput ingestion, durability, and cost-efficiency
• Improve data tiering and lifecycle policies for moving and querying data efficiently across hot, warm, and cold storage tiers
• Reduce operational costs through intelligent storage layout, compaction strategies, and query execution optimizations

Distributed Query & Execution Engine

• Improve and scale our distributed query execution engine, optimizing it for multi-source federated queries and data lake processing
• Enhance query performance across object storage (e.g., S3, GCS, Azure Blob) by optimizing indexing, partitioning, and compaction techniques
• Implement workload-aware autoscaling for query execution and data processing
• Reduce incident rates by improving system resilience, failover mechanisms, and observability

Technical Leadership & Mentorship

• Guide architectural decisions and lead design reviews across engineering teams
• Mentor engineers in distributed systems, data storage optimization, and operational excellence
• Partner with Product Management to define the technical roadmap for storage and data federation solutions
• Participate in on-call rotation, providing senior oversight for incident response and postmortem retrospectives

• 10+ years experience in software engineering, with a focus on backend and distributed storage systems
• Expertise in large-scale storage systems, such as distributed databases, cloud object storage (S3, Azure Blob, GCS), or data lake technologies (Iceberg, Delta Lake, Hudi, etc.)
• Strong background in designing and optimizing storage layers, indexing, and data lifecycle management
• Experience optimizing query engines for high-volume, low-latency federated data access
• Track record of improving system reliability, observability, and cost-efficiency
• Experience with Kubernetes-based deployment of distributed storage or query systems
• Proficiency in Go or Java (preferred, but not required)
• Deep understanding of query optimizers, storage formats (Parquet, ORC), and indexing strategies
• Experience with disaggregated storage and cloud-native data lake solutions
• Proven ability to lead technical initiatives as an individual contributor while mentoring senior engineers and driving technical excellence within a team.