Data Engineer

Diverge Health is dedicated to improving health access and outcomes for underserved populations. The Data Engineer will be responsible for designing and optimizing data architectures, building and maintaining data pipelines, and collaborating with various technical teams to enhance healthcare solutions.

Responsibilities:

• Experience building, optimizing, and maintaining data pipelines – in particular, data pipeline development and maintenance with Python, Snowflake SQL, and DBT. Strong examples of automating data flows and optimizing performance and reliability will demonstrate this experience, regardless of technology choices. Experience with Salesforce is a plus!
• 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 quality, reliability, handling failures, and monitoring data pipeline performance to support timely and accurate data delivery will demonstrate this experience
• Strong knowledge of common medical formats – hands on experience in integration with claims, EHRs and CRMs into data warehouses and operational systems. An understanding of claims consolidation, ICD, CPT and NDC codes are preferred as well as experience with front-end patient lookup software
• Problem-solving and optimization in data engineering – an ability to look at existing data flows, identify bottlenecks, and optimize 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
• Proven experience in complex healthcare environments – we’re looking for someone who has proven themselves in multiple environments – and with healthcare data specifically. This could be demonstrated with 7+ years of experience in data engineering and 7+ years of experience in healthcare, or by providing examples of handling the intricacies of healthcare data in highly complex environments
• Leadership, collaboration and communication within and across functional teams – work closely with data scientists, analysts, engineers, and business stakeholders to understand data needs and implement data solutions and lead a team in implementing cross-functional engineering projects simultaneously. Showcasing your cross-team collaboration and leadership to solve real business problems would demonstrate 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

Requirements:

• Experience building, optimizing, and maintaining data pipelines – in particular, data pipeline development and maintenance with Python, Snowflake SQL, and DBT
• Strong 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 quality, reliability, handling failures, and monitoring data pipeline performance to support timely and accurate data delivery will demonstrate this experience
• Strong knowledge of common medical formats – hands on experience in integration with claims, EHRs and CRMs into data warehouses and operational systems
• An understanding of claims consolidation, ICD, CPT and NDC codes are preferred as well as experience with front-end patient lookup software
• Problem-solving and optimization in data engineering – an ability to look at existing data flows, identify bottlenecks, and optimize performance and cost efficiency, when necessary
• Adaptability and eagerness to learn – excitement about learning new tools and technologies (e.g., new cloud platforms, additional ETL tools, or advanced orchestration methods)
• Proven experience in complex healthcare environments – we're looking for someone who has proven themselves in multiple environments – and with healthcare data specifically
• Leadership, collaboration and communication within and across functional teams – work closely with data scientists, analysts, engineers, and business stakeholders to understand data needs and implement data solutions and lead a team in implementing cross-functional engineering projects simultaneously
• Focus on reliable and scalable solutions – design and implement data pipelines that are not only functional but also scalable and maintainable
• Experience with Salesforce is a plus!
• Knowledge of some of our specific tools — Salesforce, 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, leadership, 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