Sr. Data Engineer

Seattle Children's•Seattle, WA

3d•$133,247 - $199,871•Hybrid

About The Position

The Senior Data Engineer builds data processing pipelines that collect, connect, centralize, and curate data from internal and external sources for the Enterprise Data Warehouse. The role uses a variety of languages and tools to integrate systems and leverages modern cloud platforms and services to create scalable, secure, and reliable solutions for moving and transforming data. The position designs, implements, tests, and deploys cloud-based data processing infrastructure. The engineer works in an Agile team setting, breaking down and estimating work and providing just-in-time design for small increments. This role supports Seattle Children’s Enterprise Analytics team and its mission to transform healthcare for children through work such as improving patient safety, predictive analysis, and lowering treatment costs. The position is hybrid in Seattle, Washington.

Requirements

Bachelor’s degree in computer science or a related field, or an equivalent combination of education, experience, and technical training demonstrating analytical and technical competency.
At least five years of technology-industry or related experience, including five years of experience in a data engineering role.
Experience building highly scalable, scaled-out architectures on large-scale database platforms.
Experience working in a complex data infrastructure environment.
Extensive, in-depth data pipeline development experience with industry-standard data integration tools.
Experience building scalable data pipelines using Spark or Spark-SQL with Airflow scheduler/executor framework or similar scheduling tools.
Experience with cloud platforms; GCP is preferred.
Experience with Google BigQuery or an equivalent platform.
Advanced SQL competency, including query optimization on large-scale database platforms.
Experience with the SDLC, including requirements gathering, analysis, architecture, design, implementation, testing, deployment, and technical support.
Experience using an industry-standard source control and project management tool.
Experience writing test cases and test scripts for data quality assurance.
Experience creating stored procedures and functions.
Experience developing dimensional data models with an industry-standard tool.

Nice To Haves

Experience in healthcare or a related industry.
Experience with GCP cloud services and data warehouse stores such as BigQuery.
Experience productizing or automating predictive models using R, SAS, Python, SPSS, or similar tools.
Experience with version control and CI/CD tools.
Familiarity with Agile frameworks and test-driven development methodology for analytic solutions.
API development experience.
Data visualization and/or dashboard development experience.

Responsibilities

Build data processing pipelines that collect, connect, centralize, and curate data from internal and external sources for the Enterprise Data Warehouse.
Use languages and tools to integrate systems and move and transform data across systems.
Develop scalable, secure, and reliable data engineering solutions using cloud platforms and services.
Design, implement, test, and deploy cloud-based data processing infrastructure.
Work in an Agile team setting; break down and estimate work and provide just-in-time design for small increments.
Support Enterprise Analytics initiatives, including patient safety, predictive analysis, and lowering the cost of treatment.