Data Engineer
Location: Hybrid in Palo Alto CA
Type: Contract
Duration: 6 months
Required Skills : SQL Epic domain knowledge. Python Spark or Pyspark APIs know how to asynch and concurrent Asynch IO is their bread and butter Manipulate JSON Documentation
What you will do
- Build endtoend data pipelines and infrastructure used by the Data Science team and others at SHC.
- Understand the requirements of data processing and analysis pipelines and make appropriate technical design and interface decisions. Elucidating these requirements will require training developing and validating researcherbuilt or vendor provided machine learning algorithms on hospital data as well as working with other members of the data science team.
- Understand data flows among the SHC applications and use this knowledge to make recommendations and design decisions for languages tools and platforms used in software and data projects.
- Troubleshoot and debug environment and infrastructure problems found in production and nonproduction environments for projects by the Data Science Team.
- Work with other groups at SHC and the Technology and Digital Solutions (TDS) group to ensure servers and system maintenance based on updates system requirements data usage and security requirements
Education Qualifications - Bachelors or Masters degree in Computer Science Engineering or related or equivalent working experience
- Bachelors or Masters degree in Computer Science Engineering or related or equivalent working experience
Experience Qualifications - 5 years experience in building data infrastructure for analytics teams including ability to write code for processing large datasets in distributed cloud environments
- Experience with SQL Spark Python PySpark
- Strong in APIs Async IO
- Experience manipulating JSON objects
- Experience with cloud deployment strategies and CI/CD
- Experience building and working with data infrastructure in a SaaS environment
Preferred Knowledge Skills and Abilities - Knowledge of multiple programming languages commitment to choosing languages based on projectspecific requirements and willingness to learn new programming languages as necessary.
- Knowledge of resource management and automation approaches such as workflow runners.
- Collaborative mentality and excitement for iterative design working closely with the Data Science team.