Cardinal Health
SeniorSpecialist,DataAnalytics
“Senior Specialist, Data Analytics at Cardinal Health. Skills: Data Analytics, Data Engineering, AI/ML, LLMs, GenAI, Data Platforms, Database Design, Data Modeling, SQL. Oversees the analytics life-cycle in order to identify, analyze and present relevant insights that drive business decisions and anticipate opportunities to achieve a competitive advantage.. Manages analytic data platforms, the access, design and implementation of reportingusiness intelligence solutions, and the application of adv”
What You'll Achieve.
identify, analyze and present relevant insights that drive business decisions and anticipate opportunities to achieve a competitive advantage; develop, recommend and communicate timely, accurate, relevant and actionable insights to support business decisions and objectives
Industry & Context.
Identified possible solutions to a variety technical problems and takes action to resolve; Applies judgment within defined parameters
What They're Looking For.
Must Have
Bachelors Degree in related field or equivalent work experience, 2+ years experience in related field, Proficiency in Microsoft Office products, Experience with innovative analytical insights, Business Requirements documentation experience, understanding of Agile development methodologies
Nice to Have
Hands-on experience with Python scripting for data engineering and automation, Experience with enterprise scheduling tools such as Airflow, UC4, AutoSys, or Control-M, Experience with AI/ML-driven data platforms, including feature engineering and data pipelines supporting analytics or machine learning workloads, Experience with Large Language Models (LLMs) and Generative AI (GenAI), use cases, or integrations (e. g. , leveraging data platforms for AI-driven insights or automation), Experience with enterprise data platforms such as GCP BigQuery, Databricks, Expertise in database design, data modeling, and performance optimization, Expert-level experience developing database objects including SQL, stored procedures, views, partitioning, indexing, and query optimization, Experience building semantic layers for analytics consumption using tools such as AtScale and/or LookML, Experience working on large-scale, business-critical data platforms, Experience leading or mentoring small development teams, Hands-on experience with DevSecOps and CI/CD practices, including tools such as GitHub, Airflow, and pipeline automation
What You'll Do.
Oversees the analytics life-cycle in order to identify
analyze and present relevant insights that drive business decisions and anticipate opportunities to achieve a competitive advantage.
Manages analytic data platforms
design and implementation of reportingusiness intelligence solutions
and the application of advanced quantitative modeling.
Applies business process knowledge and data analytics to develop
recommend and communicate timely
relevant and actionable insights to support business decisions and objectives.
Performs varied tasks using working knowledge in the application of concepts
principles and technical capabilities.
Works on projects of moderate scope and complexity.
Identifies possible solutions to a variety technical problems and takes action to resolve.
Applies judgment within defined parameters.
Receives general guidance and may receive more detailed instruction on new projects.
Work reviewed for sound reasoning and accuracy.
Hands-on experience with Python scripting for data engineering and automation.
Experience with enterprise scheduling tools such as Airflow
Experience with AI/ML-driven data platforms
including feature engineering and data pipelines supporting analytics or machine learning workloads.
Experience with Large Language Models (LLMs) and Generative AI (GenAI)
Experience with enterprise data platforms such as GCP BigQuery
Expertise in database design
and performance optimization.
Expert-level experience developing database objects including SQL
and query optimization.
Experience building semantic layers for analytics consumption using tools such as AtScale and/or LookML.
Experience working on large-scale
business-critical data platforms.
Experience leading or mentoring small development teams.
Hands-on experience with DevSecOps and CI/CD practices
including tools such as GitHub
and pipeline automation.
How You'll Work.
Team & Collaboration
Experience leading or mentoring small development teams
Communication Scope
Excellent written and verbal communication skills; ability to communicate complex technical concepts to non-technical stakeholders
Process & Methodology
Agile development methodologies
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