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Our team members are at the heart of everything we do. At Cencora, we are united in our responsibility to create healthier futures, and every person here is essential to us being able to deliver on that purpose. If you want to make a difference at the center of health, come join our innovative company and help us improve the lives of people and animals everywhere. Apply today!
Job Responsibility:
Apply advanced statistical, computational, and analytical methodologies to generate insights that enhance healthcare quality, patient experience, and overall cost efficiency
Identify relevant internal and external data sources, including emerging data streams such as sensor and smart‑meter data, geo‑location, and social media
Integrate, analyze, and interpret business‑level data from multiple systems, while building mechanisms to explore structured, semi‑structured, and unstructured datasets
Design and implement scalable, efficient, and automated processes for large‑scale data analysis, predictive model development, validation, and operational deployment
Manipulate, combine, and refine large datasets to prepare analysis‑ready data, ensuring data quality, performing feature engineering, and driving continuous data improvement initiatives
Monitor and analyze complex systems to diagnose issues and continuously optimize key performance indicators
Support the development and publication of analytics‑ready datasets to enable creation of dashboards, statistical models, and analytical deliverables
Provide end‑to‑end support on data‑related solutions—including data design, ingestion, aggregation, and consumption—for internal stakeholders and external clients
Develop algorithms and write efficient code for data processing and advanced analytics
Create experimental design frameworks to validate analytical findings or test hypotheses using statistically robust methodologies
Identify data issues, conduct root‑cause research, recommend corrective actions, and interpret trends and patterns across large, complex datasets
Collaborate with client‑facing teams to understand business requirements and develop tailored analytical or data engineering solutions
Support leadership with process improvement, team coordination, and conflict management activities
Research and integrate best practices for identifying data sources, conducting analysis, and improving analytical methodologies
Explore analytical approaches for complex business problems and execute solutions based on sound analytical strategies
Conduct research on industry trends, techniques, and data partnerships
evaluate findings to recommend enhancements to existing processes or the development of new ones
Requirements:
Over 8 years of experience in data analytics and data visualization
Proficient in integrating, analyzing, and interpreting business‑level data from multiple sources
Experienced in leading the design, development, and support of advanced data engineering solutions using Azure Databricks and Azure Synapse
Hands-on expertise with Azure Synapse, Azure Databricks, Power BI, and SQL
Strong capability in developing robust data pipelines using Azure Data Factory (ADF) and Informatica
Skilled in SQL and handling large datasets
Domain knowledge across Finance, Distribution, and Master Data Management (MDM)
Strong understanding of Lakehouse architecture, including Medallion Architecture
Bachelor’s Degree in Statistics, Computer Science, Information Technology, or a related discipline (or equivalent relevant experience)
Behavioral Skills: Critical Thinking, Detail Oriented, Impact and Influencing, Interpersonal Communication, Multitasking, Problem Solving, Time Management
Technical Skills: Advanced Data Visualization Techniques, Advanced Statistical Analysis, Big Data Analysis Tools and Techniques, Data Governance, Data Management, Data Modelling, Data Quality Assurance, Programming languages like SQL, R, Python
Tools Knowledge: Business Intelligence Software like Tableau, Power BI, Alteryx, QlikSense, Data Visualization Tools, Microsoft Office Suite, Statistical Analytics tools (SAS, SPSS3)
Nice to have:
Preferred Certifications: Databricks Data Engineering