Sharecare is the digital health company that helps people manage all their health in one place. The Sharecare platform provides each person - no matter where they are in their health journey - with a comprehensive and personalized health profile, where they can dynamically and easily connect to the information, evidence-based programs and health professionals they need to live their healthiest, happiest and most productive life. With award-winning and innovative frictionless technologies, scientifically validated clinical protocols and best-in-class coaching tools, Sharecare helps providers, employers and health plans effectively scale outcomes-based health and wellness solutions across their entire populations. We are always looking for people that value the opportunity to work hard, have fun on the job, and make a difference in the lives of others through their work every day!
Sharecare Health Data Services is a wholly owned subsidiary of Sharecare. The Data Engineer will demonstrate that they are culturally aligned with Sharecare Health Data Services, by displaying and working within the values of Servant Leadership, Family, Sharing Care, Compassion, Accountability and Respect for their leader and their peers. They will be innovative, open to change, and display honesty and integrity in all that they do.
- This is a remote position and can be located anywhere in the United States.
In partnership with senior leaders and data end users, the Analytics and Data Science Team is responsible for building out Sharecare's internal data infrastructure, iterating on data pipeline improvements, delivering on the analytics roadmap, and measuring its impact across the organization. The Data Engineers on the team are given direct ownership of key areas for Sharecare's business, and delivering meaningful outcomes is their primary measure of success. The team's stakeholders span the company and work across business areas and teams, including Sales, Marketing, Operations, Quality Control, Product Development, Human Resources, Finance, Information Technology as well as external clients.
In addition to developing reliable data pipelines for our end users, this role will initially have an opportunity to focus on improving our innovative data architecture and helping the team to integrate data from across the company and help build a single pane of glass view to drive actionable insight and analytics. If you have a passion for solving complex data engineering issues and are interested in steering your career in a meaningful direction where you will have the opportunity to work in a fast-paced environment - we want to hear from you!
The ideal candidate will be a life-long learner possessing intellectual humility, have excellent programming and data engineering skills, possess an ability to tackle a wide variety of projects including ETL/ELT development, data quality analysis, data modeling, monitoring, and automation and support the ongoing buildout of our data warehouse and analytics environments.
- Lead the design, development, and maintenance of scalable data pipelines for structured and unstructured data from a variety of sources including raw files, source systems, databases, external APIs, and cloud services.
- Add value at each step from raw data, to structured data, to data modeling, to reporting, analytics and machine learning.
- Monitor and continuously improve ELT/ELT processes to assemble large, complex data sets using clean Python and SQL code focusing on data reliability, efficiency, and quality.
- Lead deep architectural discussions to build confidence with our stakeholders and ensure customer success when creating new data solutions and products.
- Collaborate closely with the data analysts and scientists to strive for greater functionality in our data ecosystem and quickly resolve operational issues by working with upstream support groups and other engineering teams.
- Continuously research and integrate new data management and software engineering technologies into existing data structures and create POCs to constantly evolve our technology stack.
- Support compliance and regulations standards with data stewardship and data security policies.