The Lead Data Engineer responsibilites include building a data processing pipeline that collects, connects, centralizes, and curates data from various internal and external sources using a variety of languages and tools to marry systems together for the Enterprise Data Warehouse. Architect highly scalable and reliable data engineering solutions for moving data efficiently across systems; design, implement, test and deploy data processing infrastructure; perform work in an Agile team setting; and break down, estimate and provide just-in-time design for small increments of work. This role is pivotal to the mission and vision of Seattle Children’s Enterprise Analytics team to transform healthcare for children by providing patient safety, predictive analysis to cure diseases, lowering cost of treatement, etc .
- Bachelor's Degree in computer science or related field, or equivalent combination of education and experience/technical training that demonstrates analytical and technical competency
- Minimum of nine (9) years technology industry or related experience, including items such as:
- Three (3) years building out highly scalable, scaled-out architectures on large scale database platforms
- Experience working in a complex data infrastructure environment
- Experience in a technical lead position on a development team supporting integrated data solutions for a wide range of customer groups or three (3) years of experience in a senior data engineering role.
- Extensive and in depth data pipeline development experience with industry standard data integration tools
- Advanced competency in SQL with ability to optimize and mentor others to perform query optimization in large scale database environments
- Experience leading full development life cycle management, including requirements gathering, analysis, architecture, design, implementation, testing, deployment and technical support.
- Experience with any industry standard tool for Source Control and Project Management
- Experience writing test cases and test scripts for data quality assurance
- Experience creating stored procedures and functions
- Experience developing dimensional data model with any industry standard tool.
- Experience in Healthcare or related industry
- Experience utilizing Netezza, Datastage, BitBucket, JIRA, Confluence a plus
- Experience productizing/automating predictive models that use R, SAS, Python, SPSS, etc.
- Continuous delivery and deployment automation for analytic solutions using tools like Bamboo
- Familiarity with test driven development methodology for analytic solutions
- API development
- Data visualization and/or dashboard development