Research Data Engineer

About the Role

Key Responsibilities

• Collaborates with providers and other clinical and research subject matter experts, data analysts, and data scientists to understand and identify opportunities to develop well-defined, integrated, re-usable data sets that empower analytics.
• Supports the development of certified, trusted, and governed data assets and makes them accessible to data analysts as appropriate.
• Performs data modeling by evaluating structured and unstructured data and determines the most appropriate schema for new data warehouse components.
• Builds processes supporting data transformation, data structures, metadata, dependency, and workload management.
• Identifies, designs, and implements internal process improvements, including automating manual processes and optimizing data delivery.
• Codifies reusable data access patterns to speed up time to insights.
• Makes recommendations about platform adoption, including technology integrations, application servers, libraries, and frameworks.
• Builds automated, scalable, test-driven ELT pipelines.
• Utilizes software development and release management practices.
• Collaborates with other data engineers, DevOps engineers, and architects to ensure research data assets are developed and documented in compliance with operational and infrastructure standards.
• Works independently and effectively manages time across multiple priorities and projects.
• Participates in a shared production on-call support model.
• Incorporates best practices and standards and maintains a sustainable knowledgebase of technical and design documentation.

Requirements

• 2 years of experience in data engineering, business intelligence, database administration, and/or data warehousing.
• 2 years of experience using software such as SQL Server Reporting Services.
• 5 years of experience using SQL.
• Experience performing root cause analysis on internal and external data and processes to support specific business questions and identify opportunities for improvement.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• Experience manipulating, processing, and extracting value from large, disconnected datasets.
• Bachelor's degree in computer science, computer/software engineering, information technology, healthcare informatics, or related fields.
• Strong analytic skills related to working with structured and unstructured datasets.
• Highly proficient in SQL.
• Ability to work with relational SQL and NoSQL databases.
• Ability to work with data integration tools.
• Knowledge of and ability to navigate through infrastructure frameworks and terminologies.
• Awareness of cloud vendors and services.
• Ability to work with and integrate APIs and streaming data services.
• Familiarity with electronic health records and financial systems.

Nice to Have

• Experience in a healthcare environment.
• Degree in computer science, informatics, information systems, or another quantitative field.
• Understanding of Epic's clinical data model and experience with querying and supporting Clarity and Caboodle databases.
• Certification as Epic Clarity and/or Caboodle Administrator.