Report to our Engineering Manager
Define and own the long-term data architecture strategy for Unqork's core platform, covering data modeling, query design, storage topology, and access patterns across a complex data environment that includes MongoDB as well as integration with Relational and Columnar database models
Ensure the data layer meets the security, performance, scalability, and resilience requirements of enterprise-grade, mission-critical applications.
Evaluate and recommend the right database technologies, indexing strategies, caching layers, ETL and search infrastructure for each class of workload — including when to use MongoDB Atlas Search, Caching (e.g., Redis), Querying (e.g., Kafka) and Streaming components
Own the end-to-end solutions around data transfers using solutions like ETL for customers.
Own the data architecture for Unqork's AI-driven development layer — defining persistence, versioning, and query standards for AI-generated configurations.
Lead the design of declarative data models and schemas that enable non-technical users to build complex logic while maintaining strict data integrity.
Define the architectural boundary between database-layer computation (aggregation pipelines, indexing) and application-layer computation (Node.js post-processing, in-memory caching), and establish standards for which work belongs where.
Create and maintain comprehensive documentation including data architecture blueprints, indexing governance policies, query standards, and migration playbooks.
Own capacity planning and cost modeling for data infrastructure resources as Unqork scales.
Mentor and grow a team of data engineers and database engineers responsible for the health and performance of Unqork's data platform.
Establish data modeling best practices and enforce standardization across all environments — including schema conventions, index lifecycle management, and pagination contract design.
Oversee the design and operation of Unqork's database infrastructure — defining thresholds, coverage policies, write amplification limits, and manual override processes.
Drive data operational excellence by implementing and refining query performance monitoring, slow query alerting, explain plan review processes, and incident response playbooks for database degradation events.
Define and enforce data access governance — including RBAC data model standards, cache TTL policies, and the rules under which eventual consistency is acceptable vs. when strong consistency is required.
Comply with security regulations while working on data designs and patterns for Unqork platform.
Partner with Product to translate product requirements into data model decisions, and identify where relaxing a product constraint unlocks a disproportionate architectural improvement.

Requirements

10+ years of progressive experience in data architecture, database engineering, or a related field, with at least 3 years in a principal or architect-level role.
Extensive experience designing and managing enterprise-grade, multi-tenant data infrastructure for SaaS platforms.
Expert-level proficiency with MongoDB — including aggregation pipeline design, index strategy (B-tree, text, vector), replica sets, sharding, and query execution plan analysis (IXSCAN vs. COLLSCAN).
Deep, hands-on expertise with our core data technology stack:
MongoDB / MongoDB Atlas (aggregation pipelines, Atlas Search, Atlas Vector Search, sharding)
Relational/SQL Databases (Operational and Business Intelligence schema and query partners)
Redis (caching strategy, TTL design, cache invalidation, pub/sub)
Node.js (application/database boundary, worker threads, event loop awareness)
RBAC and access control data patterns (denormalization, write-time materialization, owner list caching)
AI/ML data infrastructure (semantic search, LLM-friendly schema design, columnar database design)
Proven ability to write architectural decision records that hold up over time — capturing not just the recommendation but the alternatives considered and the conditions under which the decision should be revisited.
Proven ability to lead technical teams, manage complex data migration projects, and influence cross-functional stakeholders including Product and Engineering leadership.
Strong understanding of data security principles, multi-tenant isolation patterns, and enterprise compliance requirements (SOC 2, ISO 27001).

Benefits

💻 Work from home with a remote-first community
🏝 Unlimited PTO (and the encouragement to use it)
📝 Student loan payback program
🏥 100% employer-covered medical, dental, and vision options available to you and your dependents
💸 Flexible Spending Account (FSA)
🏠 Monthly stipend toward your WFH setup, vacation, development and more
💰 Employer-sponsored 401(k) with contribution match
🏋🏻‍♀️ Subsidized ClassPass Membership
🍼 Generous Paid Parental Leave

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data architecturedatabase engineeringMongoDBaggregation pipeline designindex strategyRedisNode.jsRBACAI/ML data infrastructuredata modeling

Soft Skills

leadershipmentoringcross-functional collaborationtechnical team managementcommunication

Certifications

SOC 2ISO 27001