About Curology:
Curology’s mission is to make effective, personalized skincare accessible. We were founded by dermatologists who believe everyone should have access to skincare products that actually work. Today, our licensed dermatology providers have helped millions of patients across all 50 states make that mission a reality.
We combine expert medical care with personalized prescription formulas and dermatologist-developed skincare essentials to deliver science-backed solutions that meet people where they are. Join us in our mission to transform skin health and enhance lives—one patient at a time.
Mission of the Role:
The mission of the Senior Data Engineer is to own and evolve the data systems that power analytics, experimentation, and operational decision-making across the business. Reporting to the Director, Data & Analytics, the Senior Data Engineer will build reliable, scalable, cloud-native data infrastructure, partner closely with engineering and business teams, and help establish best practices that enable high-quality, privacy-safe data at scale. This role is ideal for an experienced, hands-on engineer who thrives in production environments and enjoys turning complex requirements into durable data solutions.
Essential Functions and Impact Areas:
- Own the end-to-end design, build, and operation of core data infrastructure that delivers trusted, timely data for analytics, experimentation, and decision-making.
- Within the first six months, lead the rebuild and stabilization of core data pipelines, establishing a reliable, well-documented foundation that enables accurate, scalable reporting and supports future analytics and experimentation needs.
- Build and operate data pipelines using our modern data engineering stack, including Hevo, Fivetran, dbt, Snowflake, Airflow, AWS (S3, Data Lake, Glue), Paradime, Monte Carlo, Hex, and AI-enabled tools such as ChatGPT, Claude, and SageMaker.
- Act as a senior technical contributor on the data engineering team, establishing best practices for data modeling, testing, observability, and production readiness.
- Partner cross-functionally with Engineering, Product, Marketing, and Operations to translate business needs into durable, automated data solutions.
- Improve developer and analyst productivity by reducing friction, standardizing tooling, and investing in self-service data capabilities.
- Drive continuous improvement of metrics, measurement, and experimentation systems to support insight generation and rapid iteration.
- Ensure all data systems are designed and operated with privacy, security, and regulatory compliance as foundational requirements.
- Support high-priority business initiatives by delivering accurate data quickly while maintaining platform stability and long-term scalability.
