Senior Engineer, Hims & Hers

• 8+ years of experience with SQL, preferably for data transformation or analytical use cases
• 4+ years of experience building scalable data models for analytical and BI purposes
• 3+ years of solid experience with dbt
• Mastery of data warehouse methodologies and techniques from transactional databases to dimensional data modeling, to wide denormalized data marts
• Solid experience with BI tools like Tableau and Looker
• Experience using version control (command-line, Git)
• Familiarity with one of the data warehouses like Google Big Query, Snowflake, Redshift, Databricks
• Domain expertise in one or more of the Finance, Product, Marketing, Operations, Customer Experience
• Demonstrated experience engaging and influencing senior leaders across functions, including an ability to communicate effectively with both business and technical teams
• Strong analytical and quantitative skills with the ability to use data and metrics to back up assumptions and recommendations to drive actions
• Ability to articulate vision, mission, and objectives, and change the narrative appropriate to the audience
• Experience working with management to define and measure KPIs and other operating metrics
• Understanding of SDLC and Agile frameworks
• Project management skills and a demonstrated ability to work autonomously

Desirable

• We're looking for a savvy and experienced Senior Analytics Engineer to build seamless data products in collaboration with our data engineering, analytics, engineering, business, and product management teams
• Take the data products to the next level by developing scalable data models
• Manage transformations of data after load of raw data through both technical processes and business logic
• Create an inventory of the data sources and documents needed to implement self-service analytics
• Define quality standards of the data and partner with the analytics team to define minimum acceptance criteria for the data sources
• Data cataloging & documentation of the data sources
• Regularly meet with business partners and analytics teams to understand and solve data needs, short-term and medium-term
• Build trust with internal stakeholders to encourage data-driven decision-making
• Work with all organizations to continually grow the value of our data products by onboarding new data from our backend and 3rd party system