PHI Health is looking to create and expand its data store and architect solutions including data flows and data collection for teams across the business to support their next generation of products and data initiatives in a dynamic environment.
Requirements
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience with traditional ETL technologies such as Microsoft SSIS, Informatica, Talend, etc.
- Experience with emerging cloud data platform providers such as Microsoft Fabric, Snowflake, Databricks, etc.
- Experience with distributed processing technologies like Apache Spark engine and its various querying languages such as PySpark, Spark SQL, etc.
- Experience building data pipelines, architectures, and data sets with little to no documentation and across main domains.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
Responsibilities
- Create and maintain data pipelines, data flows, PySpark notebooks, and semantic models.
- Assemble complex data sets from multiple domains to meet functional and non-functional business requirements.
- Identify, design, and implement internal process improvements: running manual processes, automating manual processes, improving data delivery, re-designing infrastructure for greater scalability, etc.
- Build the processes required for extraction, transformation, and loading of data from a wide variety of data sources including SQL, web APIs, and spreadsheets.
- Keep our data separated via access for diverse use cases including HIPAA, personally identifiable information, and financial.
- Create data tools for analysts and domain experts to assist them in building and improving the company’s services as an innovative industry leader.
- Work with domain experts and analysts to improve the company’s use of the value extracted from our data systems.
Other
- High level of customer responsiveness, excellent documentation and communication skills and attention to detail.
- Collaborate with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Responsible for the completion of long-term IT data projects with competing priorities.
- 5+ years of experience in a Data Engineer role, quantitative field.
- Experience supporting and working with cross-functional teams in a dynamic environment.
