We're a world-class team of product builders, engineers, data scientists, growth hackers, user researchers, designers, and medical experts — all building an app that generates long-term value for our millions of users worldwide. Our engineers aren’t just building a better product; they’re making the world a better place by improving access to important health information. We leverage machine learning and AI to provide accurate cycle predictions and relevant, personalized, and medically credible health tips.

About the Role

Join our Data Platform team as a foundational architect of the data infrastructure powering insights for 400M+ users globally. You'll be part of a product-focused engineering team building a modern data platform on Databricks and AWS that enables analytics, ML models, and experimentation across the organization.

We're not a service team; we're the architects of a product suite dedicated to empowering every corner of our organization with actionable insights. Our expertise in Data Engineering and Data Quality isn't just a badge of honor; it's the cornerstone upon which our company's analytics and data pipelines stand tall.

As a Staff Data Platform Engineer, you'll take ownership of critical data infrastructure components, mentor engineers, and drive projects that directly impact product decisions affecting women's health worldwide.

What You'll Accomplish

Technical Delivery:

• ​​Build and optimize data infrastructure on Databricks, ensuring sub-second query performance for analytics workloads
• Engineer robust data quality frameworks that maintain >99.9% data accuracy for ML model training and health insights
• Develop feature engineering pipelines supporting ML models that predict cycles and provide personalized health recommendations
• Optimize platform costs through efficient data architecture, storage strategies, and compute resource management

Leadership & Collaboration:

• Lead end-to-end delivery of major platform features from design through production deployment
• Partner with ML engineers, data scientists, and analytics teams to translate requirements into scalable technical solutions
• Contribute to architectural decisions and engineering best practices for the Data Platform team
• Participate in on-call rotation, ensuring platform reliability and rapid incident resolution

What We're Looking For

Required

• 8+ years of software/data engineering experience with a proven track record of building production data systems
• Expert-level proficiency in Python or Scala for data engineering workflows
• Deep hands-on experience with Apache Spark (optimization, performance tuning, debugging complex jobs)
• Production experience with modern Data Lakehouse platforms (Databricks strongly preferred)
• Strong understanding of data warehousing concepts, dimensional modeling, and ETL/ELT patterns
• Cloud platform expertise in AWS (S3, EC2, IAM, networking) or Other
• Experience with orchestration tools (Airflow, Databricks Workflows, or similar)
• Solid understanding of SQL and relational database concepts
• Track record of delivering complex projects independently with minimal guidance
• Strong communication skills and ability to explain technical concepts to diverse audiences

Strongly Preferred

• Databricks certification or deep Unity Catalog experience (metastore architecture, data governance features)
• Experience with data quality frameworks (Deequ or similar)
• Infrastructure-as-Code experience (Terraform)
• Experience with streaming data processing (Kafka, Spark Streaming)
• Data modeling expertise (Kimball, Data Vault, or similar methodologies)
• Cost optimization experience in cloud data platforms

Nice to Have

• Experience with semantic layer tools (Looker, dbt, Cube.dev)
• Feature store implementations (Tecton, Databricks Feature Store, Feast)
• Experimentation platform infrastructure
• Python for ML engineering (pandas, scikit-learn)
• Experience in building Agentin AI solutions

Why This Role is Unique

• Mission-driven impact: Your work directly supports women's health globally, powering insights that help millions make informed decisions
• Technical complexity: Handle sensitive health data with strict privacy requirements while maintaining high performance and accuracy
• Scale challenges: Build systems processing data from 400M+ users with diverse health patterns
• Innovation opportunities: Work at the intersection of data engineering, ML, and healthcare technology
• Growth trajectory: Clear path to Principal Engineer role with expanding scope and influence

Team & Culture

You'll join a 6+ person Data Platform team reporting to the Data Platform Engineering Manager. We work closely with:

• Analytics teams supporting product and business decisions
• Backend engineers integrating data pipelines with production systems
• ML Engineering, team building predictive health models
• Analytics Engineering, team defining data modeling and BI architecture
• Data Scientists developing new features and experiments

We value:

• Engineering excellence: High code quality, thorough testing, thoughtful architecture
• Collaboration: Cross-functional partnerships and knowledge sharing
• Ownership: Taking responsibility for outcomes, not just outputs
• Continuous learning: Staying current with data engineering best practices
• Work-life balance: Sustainable pace with flexible working arrangements