Imaging Data Engineer III

Children’s Hospital of Philadelphia•Philadelphia, PA

4d•Onsite

About The Position

The Center for Data-Driven Discovery in Biomedicine (D3b) at Children’s Hospital of Philadelphia (CHOP) is seeking an experienced Data Engineer to join the Translational Imaging Research Unit (TIRU). This role supports multi-institutional healthcare, research, and clinical trial initiatives by managing databases, building data integrations, developing data best practices and governance, performing reporting and data visualization, and optimizing data flow. The Data Engineer will leverage existing technologies for the complete data lifecycle, collaborate with various teams including external collaborators, and communicate with stakeholders. The ideal candidate is experienced in optimizing and building data systems from the ground up, supporting developers, architects, analysts, and scientists to ensure optimal data delivery. They will also assist non-technical colleagues with clinical and non-clinical imaging data. The role requires self-direction and comfort supporting multiple teams and systems, with an opportunity to redesign the company's data architecture. The successful candidate will have experience in Python, RESTful APIs, and Github, communicate effectively, and enable teams to transform data into insights. Experience with medical imaging data (DICOM), database management, AWS, and handling big data in biomedical contexts is strongly preferred. Continuous integration and continuous deployment experience is a bonus.

Requirements

Bachelor's Degree - Required
At least six (6) years Data Engineering/Business Intelligence/Data Warehousing experience - Required
Strong analytic skills related to working with structured and unstructured datasets.
Must possess critical thinking and creative problem solving skills along with the ability to communicate well with stakeholders throughout the organization.
Strong communication, project management and organizational skills.
Highly proficient in SQL
Experience with relational SQL and NoSQL databases, including IBM PDA (Netezza), MS SQL Server and HBase.
Experience with data integration tools: Informatica, MS Integration Services, Sqoop, etc.
Experience with cloud vendors and services: AWS, Google, Microsoft, IBM
Experience with stream-processing systems: IBM Streams, Flume, Storm, Spark-Streaming, etc.
Experience consuming and building APIs
Experience with object-oriented/object function programming languages: Python, Java, C++, Scala, etc.
Experience with statistical data analysis tools: R, SAS, SPSS, etc.
Experience with visual analytics tools: QlikView, Tableau, Power BI etc.
Experience utilizing Agile methodology for development

Nice To Haves

Master's Degree Computer Science, Informatics, Information Systems or another quantitative field - Preferred
At least six (6) years Data Engineering/Business Intelligence/Data Warehousing experience in a healthcare environment - Preferred
At least ten (10) years Data Engineer role - Preferred
Imaging (DICOM) or other biomedical/life sciences data
Programming experience (Python strongly preferred) and use of APIs and RESTful web services
Tableau, R-Shiny, or similar data visualization tools
Database design and management, relational databases such as Postgres or MySQL preferred
Working knowledge of GitHub
Cloud platforms (such as Amazon Web Services and Google Cloud Platform)
Familiarity with electronic health record and financial systems. i.e. Epic Systems, Cerner, WorkDay, Infor, Strata etc.
Working knowledge of message queuing, stream processing, and highly scalable data stores.
Experience with continuous integration and continuous deployment is a bonus.

Responsibilities

Assemble and maintain large, complex imaging data sets that meet clinical research requirements. Validate data to ensure quality.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources (including ground, hybrid cloud, and cloud) using SQL and various programming technologies.
Data Integration & Modeling – evaluate structured and unstructured data, incorporate new data, determine the most appropriate schema for new fact tables, data marts, etc. while maintaining enterprise best practices and adhering to data governance standards.
Reporting – collaborate with colleagues across the enterprise to scope requests. Extract data from various data sources, validate results, create relevant data visualizations, and share with requester. Develop dashboards and automate refreshes as appropriate.
Governance / Best Practices – adhere and contribute to enterprise data governance standards. Also educates and supports colleagues in best practices to ensure that data is used appropriately.
Product Ownership – collaborate and act as the voice of the customer to offer concrete feedback and project requests as well as an advocate for analytics from within the business units themselves.
Develop analytics tools that utilize data resources to provide actionable insights, operational efficiency and other key business performance metrics.
Work with stakeholders including the Executive, Clinical, and Analyst teams to assist with data-related technical issues and support their data infrastructure needs.
Develop optimized tools for analytics and data scientist team members that assist them in building and optimizing projects into an innovative industry leader.
Proficient at integrating predictive and prescriptive models into applications and processes.
Build processes supporting data transformation, data structures, metadata, dependency and workload management.
Make recommendations about platform adoption, including technology integrations, application servers, libraries, and frameworks.
Be a critical part of an Agile Scrum software development team, ensuring the team successfully meets its deliverables each sprint.
Performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Supporting and working with cross-functional teams in a dynamic environment.