Be a data champion and seek to empower others to leverage the data to its full potential
Understand our complex data ecosystem
Work with the product team and stakeholders to translate business requirements for data across the company into a technical roadmap and architecture for the platform
Act as the leading data domain expert and owns platform data architecture
Lead the technical design and implementation of reliable, scalable, and efficient data infrastructure, data-driven products, and software solutions for external and internal customers
Provide technical leadership to define overall data engineering best practices, standards, and architectural approaches and drive technical excellence. Identify design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Create and maintain optimal data pipeline architecture with high observability and robust operational characteristics
Assemble large, complex data sets that meet functional / non-functional business requirements
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL
Work with stakeholders, including the Executive, Product, Clinical, Data, and Design teams, to assist with data-related technical issues and support their data infrastructure needs.
Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader
Requirements
7+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
Advanced working SQL knowledge and experience working with relational databases
Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets. A definite plus with healthcare experience
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
Strong analytic skills related to working with unstructured datasets
Build processes supporting data transformation, data structures, metadata, dependency, and workload management
A successful history of manipulating, processing, and extracting value from large disconnected datasets
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
Strong project management and organizational skills
Experience supporting and working with cross-functional teams in a dynamic environment