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Role Description

As a Senior Platform Engineer on the Data Platform team, you will be responsible for designing, implementing, and maintaining the data models, data access patterns, contracts, database infrastructure, and instrumentation that power our transactional systems. You will be at the intersection of every major engineering initiative, working across Product Engineering, Analytics, ML, and Platform to set the bar for data quality, consistency, usability, scalability, and security. You will ensure great data starts at the moment a feature is built, not as a cleanup task afterward. You'll also own one of the team's most impactful initiatives: designing and migrating to modern data models that reflect how our business works at scale.

We’re a team of passionate, forward-thinking professionals eager to take on the challenge of the mental health crisis and play a formative role in providing life-saving solutions. If you’re inspired by our mission and energized by the opportunity to increase access to mental healthcare and profoundly impact millions of lives, apply today.

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

• 4+ 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-Haves

• 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.
• Total target base compensation for this role will be between $150,000 and $220,000 per year.
• Pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations.
• Cash compensation is only part of the total compensation package, which may include stock options and other Charlie Health-sponsored benefits.