Sr. Data Engineer
Nashville
Wellvana
The phase out of fee-for-service is accelerating. Value-based care offers new financial opportunities while also creating administrative challenges. Everyone needs a partner – from independent physicians to integrated health systems. Even...The Why Behind Wellvana:
The healthcare system isn’t designed for health. We’re designed to change that. We’re Wellvana, and we help doctors deliver life-changing healthcare.
Through our elevated value-based care programs, we’re revitalizing an antiquated system that’s far too long relied on misaligned incentives that reward quantity of care not the quality of it.
Our enlightened approach—covering everything from care coordination to clinical documentation education to marketing— ties the healthy outcomes of patients directly to shared savings for primary care providers, health systems and payors.
Providers in our curated network keep their independence, reduce their administrative headaches, and spend more time with patients. Patients, in turn, get an elevated experience with coordinated care between appointments that is nothing short of life-changing.
Named a 2024 "Best in Business" and 2023 "Best Place to Work" by Nashville Business Journal, we’re one of the fastest-growing healthcare companies in America because what we do works. This is the way medicine is meant to be.
Clarity on the Role:
As a Sr. Data Engineer, you will be a crucial part of the Wellvana technology team responsible for the data platform and pipelines used across the organization. You’ll work closely with our engineers, business analysts, medical economics team, actuaries, and more to help define and evolve our platform to meet the growing and changing needs of the business.
What's Expected:
- Design, build, and maintain scalable data pipelines from scratch.
- Optimize existing data pipelines for performance, reliability, and efficiency.
- Architect and manage cloud-based data infrastructure
- Utilize data orchestration tools to schedule and monitor workflows.
- Develop and optimize complex SQL queries and scripts for data processing.
- Design and implement real-time data streaming solutions.
- Build and maintain API-based data integrations to facilitate seamless data exchange between systems.
- Work with data processing frameworks for efficient data transformations.
- Implement best practices for data modeling, governance, and security.
- Deploy and manage containerized applications using Kubernetes.
- Develop and maintain CI/CD pipelines to streamline data deployment and integration processes.
- Collaborate with cross-functional teams, including analytics, product, and engineering, to ensure data availability and quality.
- Stay current with industry trends and emerging technologies to continuously improve data engineering practices.
Education
- Bachelor’s degree in Computer Science, Management Information Systems, or a related field, or equivalent experience
Years of Related Experience
- 4+ years of data engineering experience
- 3+ years of cloud engineering experience
- 2+ years of senior product management experience
- 3+ years of Python and SQL experience
- dbt experience is a plus
- Health care data experience is a plus
Skills
- Strong expertise in Python, dbt, and SQL for data transformation and manipulation.
- Proficiency in data orchestration tools like Apache Airflow or Dagster.
- Experience working with data warehouses such as Snowflake.
- Proficiency in big data technologies such as Apache Spark.
- Experience with real-time data streaming technologies like Kafka is a plus.
- Strong understanding of API-based data integrations.
- Knowledge of CI/CD practices for data engineering.
- Familiarity with containerization tools like Docker and Kubernetes.
- Strong analytical and problem-solving skills with the ability to work in a fast-paced environment.
- Excellent communication skills.
- Experience with workflow automation and data governance best practices.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow APIs Big Data CI/CD Computer Science Dagster Data governance Data pipelines dbt Docker Economics Engineering Kafka Kubernetes Pipelines Python Security Snowflake Spark SQL Streaming
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