Remote
Manager of Data Engineering & Delivery (Data Science Production Engineering)
About this role
This is an exciting opportunity to lead a Data Engineering & Delivery (DED) team at Natera, a global leader in precision medicine and genomics testing. As a Manager of the DED team inside our Data Science Production Engineering (DSPE) department, you will have the opportunity to work with Natera's diverse and ultra-large data sets (up to PB size), develop innovative solutions with the latest information and cloud technologies, and make real impact by providing timely, accurate, and robust data products and data delivery/automation systems to support Natera's Lab Operations and Genetic Counselor/Lab Director teams, and ultimately impact patients' medical outcomes.
PRIMARY RESPONSIBILITIES: Leadership Lead a Data Engineering & Delivery (DED) team, collectively develop and maintain the data infrastructure, data ingestion solutions, ETL pipelines, robust data products, and data delivery solutions, for both production support and DSPE internal applications. Manage the Data Engineering & Delivery (DED) team, to achieve the timely and efficient delivery of robust data products and systems that can meet DSPE business needs and project requirements.
Measure, report, and maintain/improve operational effectiveness. Train and coach team members on new technologies, procedures, and guidelines/best practices. Technical Lead the Data Engineering & Delivery (DED) team, collectively develop and maintain the data infrastructure, data ingestion solutions, ETL pipelines, robust data products, and data delivery solutions, for both production support and DSPE internal applications Translate DSPE's business needs and project requirements into technical specifications and implementation plans.
Working with DSPE leadership teams, create design documents that can be efficiently implemented and maintained, for data system architecture, data ETL pipeline, data delivery solution, and other data systems/tools/components. Contribute to key development, testing, deployment, validation, maintenance, and update activities on data products and data systems/tools/components, as well as data delivery tasks. Quality, Compliance, and Documentation Improve and enforce operating procedures for compliance, quality, and efficiency.