Senior Analyst, Hub Data & Analytics

New

JobgetherHealthcare analytics

Based in the United StatesFull-TimeSenior

SalaryAnnual base salary ranging from $97,900 to $133,500

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Job Details

Experience: At least 5 years of experience
Required Skills: SQLBusiness IntelligenceMicrosoft Power BIDatabricksData analytics

Hold a bachelor's degree.
Have at least 5 years of experience in analytics, business intelligence, data strategy, consulting, or a related discipline.
Have strong hands-on SQL experience querying, transforming, integrating, and analyzing complex datasets.
Have experience developing analytics and self-service solutions using Power BI, Databricks dashboards, or comparable platforms.
Translate complex or ambiguous business questions into structured approaches and practical recommendations.
Have experience working with business stakeholders to define requirements, KPIs, business rules, and analytical methodologies.
Explain technical concepts and analytical findings to business leaders in writing and verbally.
Work independently and adapt to an evolving business environment.
Manage complex initiatives with strong organization and attention to quality and measurable outcomes.
Experience in specialty pharmacy, pharmaceutical hub services, patient services, specialty medications, or related healthcare operations is preferred.
Familiarity with healthcare datasets, including pharmacy, claims, patient, provider, and benefits information, is preferred.
Knowledge of data governance, stewardship, metadata, data lineage, business definitions, and data-quality management is preferred.

Develop dashboards, reports, datasets, and decision-support tools using Power BI, Databricks, SQL, and other analytics platforms.
Work with business leaders to translate strategic and operational challenges into analytical approaches and recommendations.
Establish KPIs, business definitions, measurement methodologies, and reporting frameworks.
Support data governance and stewardship by defining ownership, quality standards, documentation, and appropriate data usage.
Partner with Technology teams and stakeholders to build trusted data assets and analytical capabilities.
Design and prototype analytical solutions, including potential external-use capabilities, and support their transition to production.
Identify and resolve data-quality issues, inconsistencies, and source-of-truth challenges.
Manage analytical initiatives from problem definition through development, implementation, and performance measurement.

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