Position: Healthcare BI Analyst
Rate: $53-$57 per hour W2
Location: Malvern, PA - Remote and requires to report 1 time a month onsite
Business Intelligence QA Analyst I - MUST have Healthcare/Hospital environment experience.
Duties:
Review requirements and design documents with developers and quality assurance manager to confirm expected functionality with technical and business needs.
Implementation, evaluation, and documentation of the developed test cases and scenarios.
Determine test environment and test data requirements, often in concert with integrated systems’ owners.
Must be able to communicate with leads regarding project readiness, status and potential risks. Document, quantify, and elevate risks as appropriate. Provide statistical reporting and analysis as necessary.
Assimilates information quickly, communicates complex requirements and issues clearly and concisely. Able to analyze root cause of a problem and demonstrate good sense when handing the problem over to development.
Tracks and coordinates defect resolution and retesting, quantifying and mitigating risk accordingly.
Enthusiastically collaborates with business partners to ensure the Mission and Core Values are fulfilled.
Skills:
Knowledge of data mining, statistical analysis or healthcare data analytics.
Experience working with development team from the initial development of business requirements, through all the Agile/Scrum steps and providing on-going maintenance and support.
Experience with Informatica Power Center, Tableau, Cognos, Anaplan
Knowledge of Software testing processes and automated tools, with an ability to apply software testing methods and techniques in a business intelligence environment.
Provide staff mentoring and guidance to foster a strong team atmosphere with an eye to customer service.
Excellent critical thinking, negotiation and problem solving skills.
Strong experience in writing SQL statements (DML/ DDL)
Knowledge of relational databases - can navigate and extract data
Prior working knowledge and validation of IBM Unified Data Modelfor Healthcare
Ability to effectively and professionally communicate, both orally and in writing, while also articulating and translating technical language to non-technical customers. Capable of influencing at all levels across the company within span of control.
Exemplifies teamwork and serves as role model, while also successfully facilitating collaboration across multiple functions, departments and levels. Unquestionable ethics & integrity is pertinent.
Track record of consistently driving projects to completion and taking accountability for work and results, as well as confronting tough issues and situations.
Demonstrates and promotes creativity and innovation. Proactively seeks out alternative solutions to business problems.
Consults with clients and teammates to identify all facets of an issue and generate a solution. Understands potential impacts to processes and systems across organization and factors these into solution
Education:
1. Participate in discovery meetings, provide estimates, analyze and validate project requirements and technical specifications, perform impact analysis and document key issues.
2. Develop the testing strategy and manage the testing effort. Evaluate data changes and anomalies against previous tends; and provide guidance to resolve variances.
3. Conduct peer reviews of other analysts' work to assure testing meets specifications. Resolve issues and develop benchmarks for testing data and provide metrics reporting on test execution and defects. Participate in testing including Functional Testing, Results validation, Regression Testing, System, Integration Testing, Automated Testing and User Acceptance Testing.
4. Communicate with data warehouse team (business analysts, data modelers and developers) regarding status, issues and risks on a timely basis. Identify, mitigate and drive project issues and risks to resolution.
5. Analyze data trends, draw conclusions and recommend direction. Develop algorithms for capturing data changes and trends to facilitate continuous monitoring of data quality.
6. Establish validation benchmarks and automated processes for data quality improvements for the weekly/monthly validations and data quality checks to ensure data is accurate for analytics. Develop trending reports and data quality metrics for reporting.
