Data Engineering Manager

About the role

Join Doximity, the leading digital platform for healthcare professionals. As a Data Engineering Manager, you will collaborate with product managers, data analysts, and machine learning engineers to develop pipelines and ETL tasks. You will establish data architecture processes and practices, inform data team strategy, and manage individual Data Engineers. Enjoy competitive health insurance, equity grants, remote working options, and more. Key missions: Collaborer avec les chefs de produit, les analystes de données et les ingénieurs en apprentissage automatique pour développer des pipelines et des tâches ETL.. Établir des processus et des pratiques d'architecture des données qui peuvent être programmés, automatisés, répliqués et servir de normes.. Gérer les ingénieurs en données individuels pour favoriser l'apprentissage, la croissance et le succès au sein de l'entreprise. Profile: - Experienced People Manager. You have experience managing 3 or more people whereby you were accountable for their growth and success as individuals and team members - You are experienced in creating automated testing, applying design patterns, and other engineering best practices - You are an expert in Python and possess fluency in SQL and have developed maintainable data pipelines with each - See a project from end-to-end. You have led several projects, your own ideas and other's. This means from idea generation to planning, execution, through delivering - Player Coach. You are able to contribute individually, outside of your reports or team, balancing priorities between being a player (i.e. individual contributor) and a coach (i.e. manager or mentor) - Communication Extraordinaire. You excel at communicating to both technical and non-technical people, with an ability to explain complex concepts simply - Foremost an engineer. You exemplify high code quality and guide others, and have at least 5 years of industry experience as a data engineer or similar role - ML/AI–aware. You have working knowledge of how ML/AI applications are deployed and monitored, and you’re motivated to use this awareness to advance data-driven initiatives