Data Architect jobs at Mongodb in United States, New York

• Collaborate with MongoDB AMP presales team and customer stakeholders to assess legacy applications, their architecture, and dependencies
• Design target-state microservice architectures on MongoDB that meet customer business, technical, and operational requirements
• Develop modernization roadmaps using the strangler pattern to progressively replace legacy components with modern MongoDB-based services
• Define and document data synchronization strategies for hybrid (part legacy / part modernized) deployment states
• Architect solutions for integration and data consistency across the broader enterprise application landscape
• Facilitate technical workshops and discovery sessions with customer architects, developers, and business leaders
• Produce presales deliverables including initial solution architectures, modernization proposals, and presentations to communicate design merits
• Produce post-sales detailed technical designs and guide MongoDB services teams and customer teams during implementation
• Provide architectural governance and direction throughout modernization projects to ensure quality, scalability, and best practices

• 8+ years of experience in solution architecture, enterprise architecture, or modernization-focused technical leadership roles
• Proven track record of designing and delivering modern, cloud-native, microservices-based architectures
• Hands-on experience with application modernization strategies, including the strangler fig pattern, domain-driven design, and event-driven architectures
• Demonstrated experience with data architecture, including migration, synchronization, and integration patterns for heterogeneous systems
• Familiarity with at least one of the legacy technology ecosystems being modernized:
• RDBMS-centric applications (PL/SQL, T-SQL)
• Monolithic Java or .NET applications
• Strong customer-facing skills: ability to facilitate workshops, present designs, and influence technical decision-making
• Experience working across both presales (solutioning, proposals) and delivery (detailed design, governance)
• Excellent communication, presentation, and documentation skills
• Willingness to travel as needed for customer engagement (approximately 25% travel)

• Ideally 8 to 11 years of related experience in a customer facing role, with 5 to 7 years of experience in pre-sales with enterprise software
• Minimum of 3 years experience with modern scripting languages (e.g. Python, Node.js, SQL) and/or popular programming languages (e.g. C/C++, Java, C#) in a professional capacity
• Experience designing with scalable and highly available distributed systems in the cloud and on-prem
• Demonstrated ability to work with customers to review complex architecture of existing applications, providing guidance on how to improve by leveraging technology
• Excellent presentation, communication, and interpersonal skills, with the ability to convey complex technical and business concepts in a clear and compelling manner to technology and business leadership
• Ability to strategize with sales teams and provide recommendations on how to drive a multi-threaded account strategy, aligning other MongoDB and ecosystem resources to move towards a mutually beneficial account plan
• The ability to travel up to 25%
• A Bachelor’s degree or equivalent work experience

• Experience selling databases and/or deploying applications with any of the major cloud providers
• Experience with database programming and data models
• Experience in data engineering or AI/ML projects
• Experience in transforming legacy systems and platforms into modern, scalable, and efficient technology stacks
• Understanding of popular sales methodologies/ frameworks such as MEDDPICC/ Command of the Message
• A MongoDB Certification
• A Cloud Provider Certification

In this role, you will work on complex opportunities where analysis of situations or data requires an in-depth evaluation of various factors. You will:

• Design and Architect: Design scalable and performant applications, systems and infrastructure for large software projects leveraging MongoDB
• Customer Advising and Value Articulation: Guide customers on architecture patterns and optimisation strategies for MongoDB, while clearly communicating its business value to the relevant stakeholders
• Sales Partnership: Collaborate with the sales team to drive account success through account planning, opportunity prioritization/qualification and pipeline generation strategy, while taking ownership of the technical aspects (including but not limited to technical discovery, demos, proof of value, presentations, sizing and documentation)
• Demand Generation: Proactively generate demand within the sales territory through self-driven technical initiatives, participation in events such as industry trade shows and account-based marketing events
• Customer Success: Foster strong customer relationships, build champions and ensure customer success and satisfaction
• Innovation and Improvement: Continuously seek opportunities to innovate and improve MongoDB solutions and processes (e.g. by relaying field feedback to the product team), as well as proactively mentor other Solutions Consulting team members
• Personal Training and Development: Engage in ongoing training and professional development to stay abreast of MongoDB product suite as well as industry trends

• Core Database Server: Master the fundamentals and advanced features of MongoDB's core database
• Atlas and Advanced Services: Gain expertise in Atlas (fully managed cloud database service), Atlas Stream Processing, Atlas Data Lake, Atlas Full-Text Search, Atlas Vector Search, and Charts
• Relational Migrator: Learn to migrate from relational databases seamlessly

• Hyperscaler Ecosystem: Gain expertise in designing complex systems utilizing cloud services on hyperscaler platforms
• Complementary Technologies: Enhance your skills with partner and complementary technologies such as Apache Kafka and Kubernetes

• Design Patterns and Methodologies: Embrace best practices in microservices, DevOps, cloud, and security
• Cutting Edge RAG and AI Architectures: Help customers on their generative AI journeys and working with industry leading partners in the space

• Effective Communication: Master presentations, demonstrations, and whiteboarding
• Client Interaction: Develop strategies for discovery and objection handling

• Diverse Market Verticals: Gain exposure to a broad spectrum of interesting use cases across various industries

• 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

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

• You have worked on production-grade building applications and are capable of making backend improvements in languages such as Python and Go
• You have experience building tools and platforms for business users and software developers
• You have experience with or working knowledge of cloud platforms and services
• You enjoy working on full stack applications including UI/UX, API Design, databases and more
• You’re looking for a high impact and growth role with variety of opportunities to drive adoption of data via services and tooling
• You’re passionate about developing reliable and high quality software
• You’re curious, collaborative and intellectually honest
• You’re a great team player

• Design and build UI, API and other data platforms services for data users including but not limited to analysts, data scientists and software engineers
• Work closely with product design teams to make improvements to the internal data platform services with an emphasis on UI/UX
• Perform code reviews with peers and make recommendations on how to improve our code and software development processes
• Design boilerplate architecture that can abstract underlying data infrastructure from end users
• Further improve the team’s testing and development processes
• Document and educate the larger team on best practices
• Help drive optimization, testing, and tooling to improve data platform quality
• Collaborate with other software engineers, machine learning experts, and stakeholders, taking learning and leadership opportunities that will arise every single day

• You have experience with modern Javascript environment including frontend frameworks such as React and Typescript
• You are familiar with data infrastructure and toolings such as Presto, Hive, Spark and BigQuery
• You are familiar with deployment and configuration tools such as Kubernetes, Drone, and Terraform
• You are interested in web design and have experience directly working with product designers
• You have experience designing and building microservices
• You have experience building a machine learning platform using tools like SparkML, Tensorflow, Seldon Core, etc.

• In three months you will have familiarized yourself with much of our data platform services, be making regular contributions to our codebase, will be collaborating regularly with stakeholders to widen your knowledge, and helping to resolve incidents and respond to user requests
• In six months you will have successfully investigated, scoped, executed, and documented a small to medium sized project and worked with stakeholders to make sure their user experiences are vastly enhanced by implementing improvements to our platform services
• In a year you will have become the key person for several projects within the team and will have contributed to not only the data platform’s roadmap but MongoDB’s data-driven journey. You will have made several sizable contributions to the project and are regularly looking to improve the overall stability and scalability of the architecture

MongoDB is growing rapidly and seeking a Data Architect to be a key member of a growing Data Architecture team; overseeing the governance, management and stewardship of data across the organization. As a Data Architect, you will be the bridge between the business and data engineering teams. You will design data models and schemas to produce high-performing, curated datasets in a mixed SQL and NoSQL environment, and drive the implementation to completion. You will populate an enterprise data catalog with key technical and business metadata driving data discoverability, and facilitate the adoption of enterprise data governance policies and procedures.

This role will be based remotely in Austin, New York City, Seattle, or California.

• At least 3 years experience building data models to support structured and semi-structured product data including telemetry
• Highly proficient in SQL. MQL (MongoDB Query Language) knowledge is a plus
• Experienced with at least one distributed query engine or cloud-based data warehouse, such as Trino or BigQuery
• Customer focused, understanding that delivering business value is of utmost importance
• Skilled at eliciting requirements and communicating across a diverse set of engineers and partners
• Familiarity with Python and rudimentary Prompt Engineering
• Well-versed in core data lake, data warehousing and data security concepts
• Familiar with data catalog functionality, business glossaries, metadata management and data lineage
• Familiar with cloud computing concepts and big data storage formats such as Parquet and Iceberg
• Capable of juggling multiple projects simultaneously
• A lifelong learner who strives for continuous improvement

As a Data Architect, you will:

• Partner with Product Owners and other Stakeholders to document data requirements, utilizing your experience to provide insights and add value to the process
• Validate and assess incoming product telemetry data, ensuring alignment with documentation and meeting Product Owners and other Stakeholders' expectations by thorough cross-referencing and testing
• Design data models and schemas within the internal data lake and data warehouse that will be used for analytical and data science consumption
• Create and execute test plans to ensure data is accurate and performance meets SLAs
• Scope and create SQL-based pipelines prioritizing data consistency and accuracy
• Implement data security standards for data access
• Document metadata and lineage in the enterprise data catalog, promoting self-service data discovery and exploration

• In 3 months, you’ll have fully ramped with our Business and Data teams
• In 6 months, you’ll have delivered at least one fully documented data model that provides value to the business
• In 12 months, you’ll have delivered multiple data models across a variety of use cases, and are comfortable working with all aspects of our internal data platform

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.