Calm
Data Engineer
Los Angeles
Calm is dedicated to guiding individuals through every stage of their mental well-being journey. As the leading app for sleep, meditation, and relaxation, Calm provides a growing collection of science-backed digital mental health programs, offering reliable support for both individuals and organizations. The flagship app delivers tailored content and activities—featuring expert insights and well-known voices—to help users reduce stress, enhance sleep, and cultivate mindfulness. For workplaces and healthcare providers, Calm offers accessible, clinically validated resources that comply with HIPAA, fostering better health and organizational results. Recognized as one of TIME’s 100 Most Influential Companies, Calm serves over 150 million people and 3,500 organizations worldwide, supporting seven languages across 190 countries.
Our Data Team
As a data-driven organization, we turn data into a strategic asset for Calm. Our team is product-focused, collaborative, and aligned with our mission to promote global happiness and health. We partner closely with cross-functional teams, including product, finance, marketing, and data science, continuously striving for improvement.
Your Role
We seek a proactive Data Engineer who thrives in ambiguity, identifies key priorities, and delivers solutions balancing speed and sustainability. You’ll work with diverse data sources—application events, product databases, and third-party data—to empower stakeholders in product development and business decision-making. Our tech stack spans AWS and GCP, utilizing tools like Airflow, Databricks, BigQuery, Postgres, and dbt.
Key Responsibilities:
Collaborate with stakeholders to understand objectives, challenges, and decision-making needs
Develop standardized data solutions to address common organizational challenges
Implement observability and testing best practices in projects
Establish processes to ensure data reliability and comprehensive documentation
Partner with analysts to refine reporting and analytical data models
Enhance data availability and accuracy for critical analysis
Past Projects:
Built a BigQuery reporting system from scratch, including data replication, infrastructure setup, dbt modeling, and reporting integrations
Developed a user-level feature store with API endpoints to support ML tasks like content recommendations and persona creation
Optimized a core data pipeline, cutting model count by 50% and runtime by 83%
Integrated our Data Warehouse with third-party apps to personalize experiences for millions of users
Redesigned orchestration to reduce critical data delivery times by 70%
Skills & Qualifications
Technical Expertise:
Proficiency in Python, Docker, Kubernetes, GCP/AWS, SQL, and data warehouses (BigQuery, Databricks, Snowflake)
Experience designing scalable data pipelines
Strong communication skills, translating technical concepts for diverse audiences
Ability to thrive in a fast-paced, agile team environment
Self-motivated with a passion for learning and problem-solving
Pragmatic approach, balancing efficiency and precision
Nice-to-Haves:
Multi-cloud experience
Familiarity with streaming systems (e.g., Segment)
Knowledge of data modeling paradigms (relational, data vault, medallion)
Exposure to Infrastructure as Code (e.g., Terraform)
Minimum Requirements:
5+ years of relevant experience
Compensation & Benefits
Calm follows a location-based pay structure, with salaries adjusted to the employee’s geographic region. For this role, the base salary ranges from 147,000to147,000to210,000, depending on qualifications, experience, and location. Compensation also includes equity, comprehensive benefits, a 401(k) plan, and flexible time off.
Inclusion & Accessibility
Calm is an equal opportunity employer, committed to fostering a diverse, equitable, and inclusive workplace. We welcome applicants of all backgrounds and provide reasonable accommodations for individuals with disabilities or special needs during the application and interview process.