Sr. Business Intelligence Analyst II

The Sr. Business Intelligence Analyst  II role is responsible for data analytics and additional support of performance measures, ongoing measurement, data collection, reporting, data visualizations and information dissemination. Responsible for implementing the strategic design and maintenance of business intelligence applications. Identifies, researches, and resolves technical problems. Ensures that the use of business intelligence applications enhances business decision-making capabilities. Engages in data exploration exercises with a variety of complex business intelligence tools, requiring knowledge of relational database structures. A resource on complex technical and business matters. Work is highly independent. Will provide a leadership role for the work group through knowledge in the area of specialization. Collaborates with other analytic teams and central engineering team as directed. Works under the supervision of a Data Trust Analytic Team Leader or other data governance or analytic leadership appropriate for the scope of work. This supervision may be through a matrixed or direct reporting structure.

Job Scope/Complexity:

• Ensures that the use of business intelligence applications enhances business decision making capabilities. Engages in data exploration exercises with a variety of complex business intelligence tools, requiring knowledge of relational database structures. A resource on complex technical and business matters.
• Work is highly independent. Will provide a leadership role for the work group through knowledge in the area of specialization. Collaborates with other analytic teams and central engineering team as directed.

Job Responsibilities:

The responsibilities listed below are typical examples of the work performed by this position. Not all duties assigned to this position are included, nor is it expected that everyone in this position will be assigned every job responsibility. The supplement page provided is an additional document  that provides information specific to the position.

• Responsible for data analytics and additional support of performance measures, ongoing measurement, data collection, reporting, data visualizations and information dissemination.

• Responsible for implementing the strategic design and maintenance of business intelligence applications. Identifies, researches, and resolves technical problems.

• Ensures that the use of business intelligence applications enhances business decision making capabilities.

• Engages in data exploration exercises with a variety of complex business intelligence tools, requiring knowledge of relational database structures.

• Serve as a resource on complex technical and business matters.

• Provide a leadership role for the work group through knowledge in the area of specialization.

• Collaborates with other analytic teams and central engineering team as directed.

• Makes appropriate decisions, using available resources, to achieve positive outcomes for patients, visitors, staff, and students in balance with sound business practice.

• Makes recommendations for changes in the current departmental systems and processes and contributes ideas and suggestions for solutions to the current system’s problems.

• Responds to urgent, impromptu, and unplanned situations by assessing their level of importance, instituting appropriate action and information appropriate management.

• Communicates decisions to appropriate management.

• Prepares incident/occurrence reports as necessary.

• Prioritizes daily tasks and assignments appropriately.

• Completes mandatory Epic and/or other software or analytic tool training as required.

• Collaborates with other analytic teams as directed.

• Data mining/management, data collection instruction, including ability to show data in a user-friendly format for a variety of audiences.

• Report and follow-up on software problems resulting in delay in workflow.

Position Overview: This position is responsible for writing and maintaining extract/transform/load routines to get data from institutional data sources for use by clinical researchers.  The position is also responsible for creating datasets from extracted “raw” data that support biostatistical analysis.

Roles & Interactions: This position will require a significant level of collaboration with the CCDA manager and other members of the CCDA team and will:

• Work closely with CCDA research customers to discern their needs and to understand and address changes that arise from end user acceptance testing.   A weekly scrum is held with the entire team to review all work.  The analyst will use Jira to document and track assignments.  Data must be delivered in a secure manner, following all applicable institutional policies and State and Federal regulations for privacy, security, and the conduct of human subject research.

• Partner with each clinical investigator, starting at the time of intake, to assess the customer’s technical and analytic capacity and connect the team to biostatistical expertise where needed to remove data roadblocks and wheel-spinning.

• Provide data-related guidance beyond data extraction, at every project phase (pre- and post-data delivery).  Post data delivery, hold data walk-through sessions, connect teams with training materials, and be on call to answer data-specific questions, ensuring that teams feel comfortable with their projected data.
• This position will follow all applicable institutional policies and State and Federal regulations for privacy, security, and the conduct of human subject research.

Specific systems, applications, projects:

• Will work with CCDA analysts on extract/transform/load projects which could last in duration from one day to several months.
• The major systems with which the position interfaces are PMAP, Epic Clarity, Epic Caboodle, CaseMix Datamart and other systems ingested into PMAP.

Scale/size of area, project and/or system supported:

• This position could work with more than one hundred different users annually, primarily from the Johns Hopkins School of Medicine, as well as the Johns Hopkins School of Public Health, Nursing, and the Engineering Program at the Homewood Campus. 
• The most complex part of this job is learning about the nuances of the data in large institutional databases, with data for approximately 7 million patients.

Additional information:

This position is remote.

Minimum Qualifications

• Bachelor’s Degree in mathematics, computer science, physics, information systems, actuarial science or related computational field.
• Six years of experience in a professional environment where the required knowledge base and skills have been utilized, and a minimum of 3 years of data analytics

• Experience in delivering effective technology solutions in a higher education environment or in the technology supported or enabled delivery of education is required.

• Requires a working knowledge of data warehouse and data management principles.

• Requires experience with data transformation and analytics projects.
• Highly skilled in developing applications using PL/SQL, JavaScript, and HTML.

• Experience with Tableau, Power BI, or other data visualization tools.
• Experience with data quality, data profiling, metadata management and reporting.
• Experience extracting, analyzing, cleaning and transform data.

• Performed data analysis, logical data modeling, created database objects, applying data normalization techniques and implementing data integrity.

Preferred Qualifications

• Master's degree in relevant discipline.
• Epic Clarity Certification

• Project management skills using Agile Methodologies using Jira/Bit Bucket
• Advanced knowledge of medical terminology and clinical informatics for positions working with patient-related data.

• Knowledge in the assigned applications as well as the platform on which it runs.
• Knowledge of healthcare and hospital business operations.
• Basic command of clinical research methods and epidemiologic principles, including missing-data handling, imputation (and its perils), parametric vs. non-parametric analysis, skewed distributions, implications of continuous vs. categorical data, assessing measurement error, form design, PID validation, CPT data, and ICD9/ICD10 diagnosis categories and handling within Epic.