Senior Application Database Engineer

WE’RE HEIDI. We're building the future of healthcare by giving every clinician the earth's finest AI Care Partner. In just 18 months, our clinical AI products have absorbed the administrative chaos of 73 million patient visits. Today, we support over 2.5 million patient sessions a week across 190+ countries. Healthcare systems are failing us; clinicians spend more time on documentation than on patients, and the human connection that makes medicine worth practicing is eroding. Our mission is simple: double the world’s healthcare capacity and strengthen the human connection at its heart. We found product-market fit with a freemium medical scribe that clinicians love. Now, we're expanding. Every task a clinician hands to Heidi is a patient who feels more attended to, a health system unclogged, and a clinician who gets to be a clinician again. If you don’t choose easy and you want to build something way bigger than yourself then, choose the challenge, choose Heidi. THE ROLE You will be the dedicated owner of our database infrastructure as we scale globally. Today that means MongoDB Atlas. Tomorrow it may include relational workloads, vector databases, cross-database migrations, and multi-region data architecture decisions. This is a hands-on engineering role that sits at the intersection of schema design, query performance, infrastructure as code, and platform reliability. If you know how to design data models around access patterns, optimize for the queries that matter, and make principled decisions about when to use which database technology, you will thrive here. WHAT YOU WILL DO - Own MongoDB Atlas cluster configuration and management across production, staging, and development environments spanning multiple regions globally across AWS and Azure - Lead schema and data model design across services, making deliberate choices around embedding, referencing, denormalization, and aggregation patterns - Own index strategy, query performance analysis, and aggregation pipeline design across all collections - Evaluate and plan database technology decisions including when MongoDB is the right fit and when a relational store like Amazon RDS is more appropriate - Design and execute data migrations between database systems as the platform evolves, writing Python tooling to support migration pipelines and data transformation - Manage all Atlas infrastructure through Terraform including cluster sizing, compute auto-scaling, private endpoints, and access control - Design and maintain OIDC authentication and workforce identity federation across Atlas projects - Own database user management, credential rotation, and access control policies - Detect and remediate infrastructure state drift between Terraform and Atlas configuration - Monitor database performance, identify bottlenecks, and drive optimisation across replica sets and sharded clusters - Partner with backend engineers on schema design, indexing strategies, and query performance - Establish runbooks for operational tasks including failover, scaling events, and incident response   WHAT YOU'LL BRING - 5+ years of experience with MongoDB in production, including Atlas-managed clusters - Strong ability to design schemas around application access patterns rather than relational conventions - Deep understanding of indexing, query planning, aggregation pipelines, and MongoDB operational fundamentals - Solid experience with Amazon RDS or other relational databases, including schema design and query optimisation - Strong SQL skills including query optimisation, indexing, and schema design for relational workloads - Proficiency in Python for scripting, automation, and data migration tooling - Experience planning or executing database migrations across technology boundaries - Proficiency with Terraform for managing cloud database infrastructure - Hands-on experience with AWS and Azure networking as it relates to private database connectivi