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.
We're looking for a savvy and experienced Senior Data Engineer to join the Data Platform Engineering team at Hims. As a Senior Data Engineer, you will work with the analytics engineers, product managers, engineers, security, DevOps, analytics, and machine learning teams to build a data platform that backs the self-service analytics, machine learning models, and data products serving Million+ Hims & Hers subscribers.
You Will:
- Architect and develop data pipelines to optimize performance, quality, and scalability.
- Build, maintain & operate scalable, performant, and containerized infrastructure required for optimal extraction, transformation, and loading of data from various data sources.
- Design, develop, and own robust, scalable data processing and data integration pipelines using Python, dbt, Kafka, Airflow, PySpark, SparkSQL, and REST API endpoints to ingest data from various external data sources to Data Lake.
- Develop testing frameworks and monitoring to improve data quality, observability, pipeline reliability, and performance
- Orchestrate sophisticated data flow patterns across a variety of disparate tooling.
- Support analytics engineers, data analysts, and business partners in building tools and data marts that enable self-service analytics.
- Partner with the rest of the Data Platform team to set best practices and ensure the execution of them.
- Partner with the analytics engineers to ensure the performance and reliability of our data sources.
- Partner with machine learning engineers to deploy predictive models.
- Partner with the legal and security teams to build frameworks and implement data compliance and security policies.
- Partner with DevOps to build IaC and CI/CD pipelines.
- Support code versioning and code deployments for data Pipelines.
You Have:
- 8+ years of professional experience designing, creating and maintaining scalable data pipelines using Python, API calls, SQL, and scripting languages.
- Demonstrated experience writing clean, efficient & well-documented Python code and are willing to become effective in other languages as needed.
- Demonstrated experience writing complex, highly optimized SQL queries across large data sets.
- Experience working with customer behavior data.
- Experience with Javascript, event tracking tools like GTM, tools like Google Analytics, Amplitude and CRM tools.
- Experience with cloud technologies such as AWS and/or Google Cloud Platform.
- Experience with serverless architecture (Google Cloud Functions, AWS Lambda).
- Experience with IaC technologies like Terraform.
- Experience with data warehouses like BigQuery, Databricks, Snowflake, and Postgres.
- Experience building event streaming pipelines using Kafka/Confluent Kafka.
- Experience with modern data stack like Airflow/Astronomer, Fivetran, Tableau/Looker.
- Experience with containers and container orchestration tools such as Docker or Kubernetes.
- Experience with Machine Learning & MLOps.
- Experience with CI/CD (Jenkins, GitHub Actions, Circle CI).
- Thorough understanding of SDLC and Agile frameworks.
- Project management skills and a demonstrated ability to work autonomously.
Nice to Have:
- Experience building data models using dbt
- Experience designing and developing systems with desired SLAs and data quality metrics.
- Experience with microservice architecture.
- Experience architecting an enterprise-grade data platform.
