Responsibilities
- Define, implement, and evolve data models and schemas in Postgres to support product and analytical use cases.
- Develop and maintain our data access standards and patterns in our core backend systems with Python and Typescript.
- Lead the definition, design, and phased migration to improved data models for core business concepts.
- Work alongside product engineering teams to deliver features with correct and well-modeled data at the source.
- Measure and improve data quality, correctness, stability, and usability improvements across our transactional systems.
- Provide options around key initiatives and break down work into visible and achievable milestones, delivering incremental value.
- Mentor and train other engineers throughout the organization and seek to continually improve our architecture and data modeling standards and engineering processes.
- Improve data usability, trust, and developer productivity by building shared tooling, patterns, and documentation that make it easy for teams to produce and consume high-quality data.
- Maintain and improve our transactional database infrastructure running in AWS.
- Review SQL and data access code for our production systems.
- Partner with engineers across the organization to ensure database migrations are executed correctly and safely.
- Profile, analyze, and tune slow or inefficient queries in Postgres.
- Leverage AI-powered tooling to enhance the software development lifecycle.
- Drive security, reliability, scalability, observability, and cost-efficiency improvements across our deployed services.
- Hands-on experience participating in an on-call rotation, responding to and resolving critical infrastructure and application issues promptly.
Requirements
- 6+ years of experience in a role focused on Backend or Data Platform Engineering.
- 3+ years of experience writing production-level SQL and backend code.
- Recent expertise with Python as a primary programming language.
- Experience with data modeling concepts and best practices (e.g., dimensional modeling, data vault, or similar).
- Experience with observability, monitoring, and logging tools such as Datadog and Cloudwatch.
- Proven track record of breaking down large problems and delivering incremental value to meet deadlines while providing options for long-term improvements.
- Ability to troubleshoot complex distributed systems.
- Familiarity with AI-enabled developer productivity tooling.
- Strong communication and problem-solving skills, and the ability to work in a fast-paced startup environment.
- Hands-on experience participating in an on-call rotation, responding to and resolving critical infrastructure and application issues promptly.
Nice to Have
- Proficiency with programming languages like Typescript or Golang.
- Experience with large data migrations on production systems.
- Expertise with AWS services like Aurora, S3, SQS, ECS Fargate, and Lambda.
- Proficiency with Snowflake as a cloud data warehouse.
- Experience with Data Engineering tools like DBT, Dagster, Fivetran, and Hightouch.
- Familiarity with event-driven data architectures and stream processing (e.g., Eventbridge, Kafka, or similar).
Benefits
- Comprehensive benefits to all full-time, exempt employees.
Work Arrangement
Hybrid
Additional Information
- Team members who live within 45 minutes of a Charlie Health office are expected to follow a hybrid work schedule.
- We currently work in Scrumban-style 2-week sprints. Our teams work hybrid (required if in NY) and remotely across time zones, but are available during core meeting hours (12PM to 5PM EST).
