Senior Data Engineer

About Us:

Function was founded with a singular focus: empower you to live 100 healthy years. We’re doing that by using the best available technology to make sure people don't suffer or die a preventable death. Function has been recognized as one of Fast Company’s Most Innovative Companies of 2024, and is venture-backed by Andreessen Horowitz (a16z). 130,000+ members have joined Function to take control of their health. We are growing our team and seeking out world-class talent that deeply believes in our mission to positively impact global health, has a relentless bias toward action and a growth mindset. Function fosters a collaborative and dynamic environment, where every day we are building the future.

Role:

We’re looking for an experienced Senior Data Engineer to design, build, and scale the systems that power analytics and decision-making across Function Health. You’ll partner closely with data scientists, analysts, and software engineers to ensure our data is accurate, accessible, and actionable — enabling every team to confidently leverage data in their work.

Key Responsibilities:

• Architect and build core data infrastructure leveraging Databricks, Spark, and modern ELT tools.
• Develop robust, maintainable data pipelines (batch and streaming) that support analytics, experimentation, and product insights.
• Build and scale self-service data tools and abstractions that empower analysts, data scientists, and business users to access and use data independently.
• Define and uphold data governance and compliance standards, including access control, lineage, and metadata management.
• Collaborate cross-functionally (product, engineering, clinical, operations) to translate business needs into reliable, performant data solutions.
• Mentor and guide team members, contributing to technical standards and best practices.
• Drive the long-term data platform vision, balancing scalability, reliability, and usability for both technical and non-technical audiences.

Qualifications/Skills:

• 6+ years of experience in data engineering, with a focus on scalable data architectures.
• Strong expertise in GCP (IAM, GCS, Pub/Sub, etc.) or equivalent cloud platform and hands-on experience with Spark and Databricks.
• Hands-on experience with CDC technologies like Fivetran, or equivalent.
• Proficiency in ETL/ELT tools and frameworks (dbt, Apache Airflow, Dataform, etc.).
• Deep understanding of data governance principles, including compliance and security best practices.
• Experience designing data models, abstractions, and self-service interfaces that improve usability and reduce bottlenecks.
• Demonstrated success in collaborating across functions to deliver data solutions for analytics, experimentation, or compliance.
• A balance of IC execution and leadership skills; you’re equally comfortable rolling up your sleeves or mentoring others.
• Familiarity with streaming data architecture, real-time ingestion, and delivery frameworks.
• Proficient in SQL and Python for data processing and automation.
• Strong problem-solving skills with the ability to work in a fast-paced environment.
• Excellent communication and technical storytelling skills — you can align technical work with business value.

Nice-to-Have Skills and Experiences:

While the core competencies are essential, the following qualifications will distinguish exceptional candidates:

• Experience with Terraform or Infrastructure-as-Code (IaC) for data infrastructure automation.
• Background in HIPAA or other regulated environments with sensitivity to data privacy and compliance.
• Familiarity with the dbt Semantic Layer and modern data modeling best practices.
• Exposure to data observability platforms and practices.
• Familiarity with machine learning data pipelines.
• Exposure to multi-cloud or hybrid-cloud environments.
• Experience building scalable solutions in a 0-1 env