Mid-Level Data Engineer

October 20

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Diverge Health

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Description

• At Diverge Health we are a team of entrepreneurs passionate about improving health access and outcomes for those most in need. We partner with primary care providers to improve the engagement and management of their Medicaid patients, providing independent practices access to specialized resources and clinical programs to address medical, social and behavioral patient needs. • Our care ecosystem is equipped with enhanced technology and data interfaces to enable provider and patient success in a value-based environment. • Guided by our core values of humility, continuous learning and feeling the weight, our team is on a mission to strengthen communities from within, unlocking people's ability to live their healthiest lives. • Reporting to the Senior Vice President, Technology, this Data Engineer will be passionate about our mission to support those who need help most in our healthcare system.

Requirements

• Experience building, optimizing, and maintaining data pipelines – in particular, data pipeline development and maintenance with Python, Snowflake SQL, and dbt. Examples of automating data flows and optimizing performance and reliability will demonstrate this experience, regardless of technology choices. • Data orchestration experience – practical experience in using data or workflow orchestration tools (such as Dagster, Prefect, Airflow, etc) to manage and schedule data workflows. Examples designing automated workflows that ensure data reliability, handling failures, and monitoring data pipeline performance to support timely and accurate data delivery will demonstrate this experience. • Healthcare data integrations with CRMs and EHRs – hands-on integrations with CRMs or EHRs into data warehouses and operational systems. This could be demonstrated by providing real-world examples of coordinating data between such systems and ensuring data accuracy and consistency across business applications. • Problem-solving and optimization in data engineering – an ability to look at existing data flows, identify bottlenecks, and optimize for performance and cost efficiency, when necessary. Provide some examples of how you’ve done this in the past. • Adaptability and eagerness to learn – excitement about learning new tools and technologies (e.g., new cloud platforms, additional ETL tools, or advanced orchestration methods). Give us samples on mastering new skills and applying them to improve data processes or pipelines. • Solid experience with a strong potential to grow – someone who may not yet be a consistent senior influencer or architect, but who has multiple examples of going beyond their experience level. This can be indicated by having 2-5 years of strong experience with some examples of going beyond the years. Tell us how you’ve solved a big problem or had a big impact – we want to know. • Collaboration and communication with cross-functional teams – work closely with data scientists, analysts, engineers, and business stakeholders to understand data needs and implement data solutions. Cases about cross-team collaboration and solving business problems would validate this experience. • Focus on reliable and scalable solutions – design and implement data pipelines that are not only functional but also scalable and maintainable. Examples of ensuring data integrity, handling data failures gracefully, and creating monitoring and alerting mechanisms are important for this role. • Experience and understanding of healthcare technology and industry trends – being familiar with the industry always helps. • Proficiency in working with healthcare players such as providers and payers – these are two of our biggest customer personas. • Background in healthcare data systems and integrations, such as EMRs, claims feeds, healthcare integrators, etc. There’s a lot of data out there, and efficiently integrating and understanding that data is critical to our success. • Knowledge of some of our specific tools helps – Snowflake, Dagster, dbt, Hightouch, Sigma, … - but it’s not a hard requirement. • Abilities and experience with other languages and technology stacks – Python, Hadoop, Glue, etc – no one tool solves every task, so having a bigger toolbelt is always a plus! • Teamwork, mentorship, and history helping teams and teammates grow and get stronger – being able to lift a coworker shows a commitment to more than oneself. • Start-up or small company experience – start-ups have no silos or boundaries like larger companies might, so showing how you’ve been in such an environment before helps prove that you can do it again.