Principal Engineer - Databases, Data Platform, MLOps
About The Position
At Lingo, we’re building a groundbreaking health platform that combines continuous biosensor data, real-time analytics, and personalized insights to help people live fuller, longer, and healthier lives. Our systems ingest millions of sensor readings daily, powering experiences for consumers and partners worldwide, with the reliability and scalability of cloud-native, enterprise-grade platforms. THE OPPORTUNITY We’re looking for a Principal Engineer to lead the technical vision for our database infrastructure and enterprise data platform. You will own architecture decisions that enable large-scale, reliable, and secure data systems spanning batch, streaming, and real-time workloads. While AI and MLOps are emerging areas for us, you’ll play a key role in laying a foundation for future machine learning capabilities. This role combines hands-on engineering with tech strategic leadership across databases and data pipelines. This is an opportunity to shape the foundation of a platform that will support millions of users globally.
Requirements
- 10+ years of software engineering experience with 7+ years focused on databases, data engineering, or ML infrastructure
- Deep knowledge of relational and NoSQL databases, query optimization, replication, and sharding.
- Experience building and operating large-scale data pipelines
- Strong SQL and data modeling skills (dimensional, 3NF, Data Vault).
- Familiarity with cloud-native data services (AWS, Azure, GCP).
- Proven ability to lead cross-functional technical initiatives.
Nice To Haves
- Exposure to vector databases (pgvector, Pinecone, Milvus) and generative AI retrieval patterns.
- Knowledge of regulated industry requirements (HIPAA, SOC2, GDPR).
- Experience with Kubernetes and containerized data workloads.
- Understanding of FinOps and data infrastructure cost optimization.
Responsibilities
- Design and maintain database systems across relational, NoSQL, and time-series technologies
- Implement performance tuning, indexing, sharding, replication, and failover strategies
- Develop standards for schema design, migrations, and capacity planning
- Architect and optimize data pipelines using Spark, Flink, Kafka, Airflow, or equivalent
- Evolve our data platform to support batch, streaming, and real-time needs as well as define backups, restore testing, patching, and security controls to ensure compliance
- Drive data quality, observability, lineage tracking, and efficient resource usage
- Coordinate with stakeholders to define and enforce data modeling practices
- Design our MLOps foundations and practices such as data preparation, reproducibility, and monitoring
- Drive integration points for future ML model deployment and vector database use cases.
- Serve as a technical anchor across data and ML domains, providing architectural guidance and code reviews for complex systems
- Author technical RFCs, architecture decision records, and engineering standards adopted across teams
- Mentor engineers, raise the bar on engineering excellence and best practices
- Collaborate with Product, Security, Compliance, and Infrastructure teams to align data strategy with business objectives
- Represent the organization in vendor evaluations, open-source community engagement, and industry forums
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
5,001-10,000 employees
