Sr. Data Engineer

Wellvana•Nashville, TN

just now

About The Position

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.

Requirements

Bachelor’s degree in Computer Science, Management Information Systems, or a related field, or equivalent 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
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.
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.

Nice To Haves

dbt experience is a plus
Health care data experience is a plus
Experience with real-time data streaming technologies like Kafka is a plus.

Responsibilities

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.