Principal Data Engineer

Hims & Hers Health, Inc. (better known as Hims & Hers) is the leading health and wellness platform, on a mission to help the world feel great through the power of better health. We are revolutionizing telehealth for providers and their patients alike. Making personalized solutions accessible is of paramount importance to Hims & Hers and we are focused on continued innovation in this space. Hims & Hers offers nonprescription products and access to highly personalized prescription solutions for a variety of conditions related to mental health, sexual health, hair care, skincare, heart health, and more.

Hims & Hers is a public company, traded on the NYSE under the ticker symbol “HIMS”. To learn more about the brand and offerings, you can visit hims.com and forhers.com, or visit our investor site. For information on the company’s outstanding benefits, culture, and its talent-first flexible/remote work approach, see below and visit www.hims.com/careers-professionals.

​​About the Role:

We're looking for an experienced Principal Data Engineer to join our Data Platform Engineering team. Our team is responsible for enabling H&H business (Product, Analytics, Operations, Finance, Data Science, Machine Learning, Customer Experience, Engineering) by providing a platform with a rich set of data and tools to leverage.

You Will:

• Serve as a technical leader within the Data Platform org. Provide expert guidance and hands-on development of complex engineering problems and projects
• Collaborate with cross-functional stakeholders including product management, engineering, analytics, and key business representatives to align the architecture, vision, and roadmap with stakeholder needs
• Establish guidelines, controls, and processes to make data available for developing scalable data-driven solutions for Analytics and AI
• Create and set best practices for data ingestion, integration, and access patterns to support both real-time and batch-based consumer data needs
• Implement and maintain data governance practices to ensure compliance, data security, and privacy.
• Design and lead development on scalable, high-performance data architecture solutions that supports both the consumer side of the business as well as analytic use cases
• Plan and oversee large-scale and complex technical migrations to new data systems and platforms
• Drive continuous data transformation to minimize technical debt
• Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
• Define and lead technology proof of concepts to ensure feasibility of new data technology solutions
• Provide technical leadership and mentorship to the members of the team, fostering a culture of technical excellence
• Create comprehensive documentation for design, and processes to support ongoing maintenance and knowledge sharing
• Conduct design reviews to ensure that proposed solutions address platform and stakeholder pain points, as well as meet business, and technical requirements, with alignment to standards and best practices
• Prepare and deliver efficient communications to convey architectural direction and how it aligns with company strategy. Be able to explain the architectural vision and implementation to executives

You Have:

• Bachelor's or Master's degree in Computer Science or equivalent, with over 12 years of Data Architecture and Data Engineering experience, including team leadership
• Proven expertise in designing data platforms for large-scale data and diverse data architectures, including warehouses, lakehouses, and integrated data stores.
• Proficiency and hands-on knowledge in a variety of technologies such as SQL, Bash, Python, Java, Presto, Spark, AWS, data streaming like Kafka, RabbitMQ,
• Hands-on experience and proficiency with data stacks including Airflow, Databricks, and dbt, as well as data stores such as Cassandra, Aurora, and ZooKeeper
• Experience with data security (including PHI and PII), as well as data privacy regulations (CCPA and GDPR)
• Proficient in addressing data-related challenges through analytical problem-solving and aligning data architecture with organizational business goals and objectives
• Exposure to analytics techniques using ML and AI to assist data scientists and analysts in deriving insights from data
• Analytical and problem-solving skills to address data-related challenges and find optimal solutions
• Ability to manage projects effectively, plan tasks, set priori