Responsible for creating and maintaining an optimal data pipeline architecture.
Responsible for data analysis and reporting/charting across multiple projects (datasets)
Highly skilled in SQL to extract/manipulate/summarize/join data from various sources for
Data Reporting/Visualization
Candidate will be responsible for ad-hoc data analysis and reporting/charting
9+ years of experience as a data engineer or in a similar role
Must be familiar with GCP BigQuery and other GCP tools
5+ years of cloud-based data architecture and/or engineering
5+ years of experience designing, developing and maintaining ETL and ELT processes
5+ years working with healthcare systems analysis/programming preferred
5+ years of data lake/enterprise data warehouse experience
Experience with several querying languages, schema definition languages, and scripting languages
Experience with writing and optimizing SQL queries in a business environment with large-scale, complex data sets
Experience with working with large data sets, data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments
Strong knowledge of various data warehousing methodologies and data modeling concepts. Hands on modelling experience is highly desired
Essential Functions
Design, implement, and automate deployment of our distributed system for collecting and processing log events from multiple sources
Design data schema and operate internal data warehouses and SQL database systems
Own the design, development and maintenance of ongoing metrics, reports, analyses, and dashboards to drive key business decisions.
Monitor and troubleshoot operational or data issues in the data pipelines.
Drive architectural plans and implementation for future data storage, reporting, and analytic solutions.
Work collaboratively with business analysts, data scientists, and other internal partners to identify opportunities/problems.
Provide assistance to the team with troubleshooting, researching the root cause, and thoroughly resolving defects in the event of an error.