Capsule is rebuilding the $425 billion pharmacy industry from the inside out with an emotionally resonant experience, and technology that enables customized outcomes for doctors, hospitals, insurers, and manufacturers. Our team makes the same promise to each other as the one we’ve made to our customers, doctors, and partners: everybody needs some looking after sometimes. We’ll never lose sight of the fact that behind all the craziness of the healthcare system, we’re just people looking after other people. Capsule has raised over $250 million from TCV, Thrive Capital, Glade Brook Capital, and The Virgin Group.
About The Role:
Capsule is looking for a hands on Data Engineering Leader to manage our data warehouse and data pipeline efforts. You will be responsible for managing the team that owns all of our batch and real time data pipelines that power Capsule’s consumer and internal applications, operational workflows, and business intelligence. This will be a hands on role to start.
Some of the things you’ll work on:
Understand and manage the data needs of stakeholders across Finance, Logistics and Product.
Develop the vision and roadmap strategy to provide proactive solutions and enable stakeholders to extract insights and value from data.
Design best practices for data processing, data modeling and warehouse development.
Evaluate new technologies and solutions to solve business problems
Build roadmaps that meet the business needs and support long term growth of the team and architecture.
Work closely with our talent team to grow this small but mighty team.
Contribute to engineering wide activities such as hiring and design review with your peers across the organization.
About the stack
Python, Redshift, Airflow, Presto, Postgres
3+ years in a leadership/management capacity around data engineering, building data warehouses and data pipelines
5+ years of relevant experience with data engineering, having experience with:
Data pipelines, ETL, data warehousing, workflow systems
AWS Redshift, Hadoop, or similar.
Databases like RDBMS, NoSQL, and SQL.
Experience managing multiple stakeholders
Experience with data architectures and data modeling
Experience with Python
Background in ETL and data processing, know how to transform data to meet business goals
Experience developing people and teams through coaching, mentoring, and feedback.
Excellent communication, adaptability and collaboration skills
Interest in working at a startup and scaling with the company as we grow.