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Job Details Position Summary:
The Data, Analytics & AI Architect actively participates in providing the overall direction of architecture across the entire data analytics ecosystem. The role is responsible for defining and driving the strategic vision for enterprise data and AI systems. This position oversees the design and implementation of scalable, secure, and innovative data platforms and AI capabilities that empower business intelligence, advanced analytics, and machine learning across the organization. This role is critical in shaping the enterprise data and analytics vision and strategy, ensuring alignment with the company's strategic business plans.
As a key member of the Data, Analytics & AI Architecture team, you will contribute to planning, design, and implementation of the enterprise data and analytics vision and strategy aligned with the company's strategic business plans. You will enable innovation and understand the business analytics trends that can create business value while decreasing time to market and reducing solution complexity.
In this role you will act as an advisor for various complex projects and initiatives and taking full ownership of all necessary architectural artifacts, high-level designs, proof of concepts (POCs), and deployment support for small to medium scope data, analytics, and GenAI solutions. You will play a pivotal role in defining the building blocks for future-state architecture and creating a roadmap for realizing these goals. You will thrive on bringing innovative approaches validated by quality research, industry insights, and proof of concepts supporting the suggested technology or architecture solution blueprint. In addition to demonstrating proficiency and a deep understanding across the four key data and analytics verticals, you will have substantial experience with data management, data security, and data operations.
Furthermore, you will possess robust expertise in ML/AI capabilities. This diverse knowledge will empower you to recommend breakthrough improvements across the entire data and analytics ecosystem, ensuring the integration of AI/ML capabilities to enhance analytics processes and outcomes.
Primary Duties & Responsibilities:
Architecture Leadership:
Responsible for developing architecture for technology including best practices and guiding principles, and design of new data and analytics technology. Partner through implementation and operational support to ensure technology is achieving desired business outcomes.
Collaborate with business and solution architectures for less complex data and analytics initiatives to ensure we achieve enterprise data and analytics objectives while meeting the business use case requirements
Experience guiding cross-functional teams and influencing senior stakeholders
Analyzes current architectures to identify weaknesses and develop opportunities for improvements
Ensure the completeness of technical requirements and functional architecture analysis for the design and implementation of data and analytics business solutions
Define, document, and maintain architecture patterns
Complete architecture solution blueprint for data and analytics initiatives
Ability to define and architect interim architectures and strategy to ultimately align to end state
Develop and present a variety of architectural artifacts and documentation
Establishes standard architectural principles, patterns, and processes
Innovation & Emerging Tech:
Participate in proof-of-concept initiatives to assess and analyze fit for purpose of potential solutions
Participate in data and analytics capability maturity assessment leveraging insights to build foundational future state architecture and corresponding roadmaps
Foster innovation by evaluating emerging technologies and recommending adoption where appropriate
Strives to continuously increase the overall data and analytics architecture practice maturity
Deep understanding of data platforms, cloud technologies (e.g., Azure, AWS, GCP), data modeling, and analytics tools
AI/ML Integration:
Model development and deployment using frameworks such as TensorFlow, PyTorch, or Scikit-learn
Familiarity with cloud-based ML platforms, such as AWS SageMaker, Azure Foundry, or Google AI Platform, Mosaic AI
Experience in utilizing tools like MLflow for managing the ML lifecycle, including experimentation, reproducibility, and deployment
Knowledge of natural language processing (NLP) and/or reinforcement learning techniques as applicable to business use cases
Ability to integrate advanced analytics and AI/ML models into existing data workflows, ensuring seamless access and usability
Skills & Knowledge:
Behavioral Skills:
Organizational Agility
Growth mindset
Creative, Innovative thinking
Customer Focus
Learning Agility & Self Development
Cross functional people management
Stakeholder management
Mentoring and coaching
Problem solving
Drives for results
Verbal & written communication
Technical Skills:
Data and Analytics computing methodologies
Data and Analytics platforms, tools, and integration processes both on-prem and cloud
Common integration patterns (batch, micro-batch, near real time, real time)
Data Fabric framework
Basic Programming skills in Python, SQL
Data management and data security
Tools Knowledge:
Data pipeline tools like ADF, IICS
Data platforms: Snowflake, Databricks, BigQuery
BI tools: Power BI, Tableau, Looker
Cloud platforms: Azure, AWS, GCP
Streaming/Event processing and pub/sub software
AI/ML Tools like MLOps, Tensorflow, Mosaic AI, AWS Sagemaker, Pytorch
.
Experience & Educational Requirements:
Bachelor’s Degree in Statistics, Computer Science, Information Technology or any other related discipline or equivalent related experience. 12+ years of directly-related or relevant experience, preferably in healthcare data analytics or data engineering. Preferred Certifications:
Advanced Data Analytics Certifications
AI and ML Certifications
SAS Statistical Business Analyst Professional Certification Skills & Knowledge:
Behavioral Skills:
Coaching and Mentoring
Decision Making
Impact and Influencing
Leadership Skills
Multitasking
People Management
Planning Technical Skills:
Advanced Data Visualization Techniques
Advanced Statistical Analysis
Big Data Analysis Tools and Techniques
Data Governance
Data Management
Data Modelling
Data Quality Assurance
Machine Learning and AI Fundamentals
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)
What Cencora offersBenefit offerings outside the US may vary by country and will be aligned to local market practice. The eligibility and effective date may differ for some benefits and for team members covered under collective bargaining agreements.
Full time
Affiliated CompaniesAffiliated Companies: AmerisourceBergen Services Corporation
Equal Employment OpportunityCencora is committed to providing equal employment opportunity without regard to race, color, religion, sex, sexual orientation, gender identity, genetic information, national origin, age, disability, veteran status or membership in any other class protected by federal, state or local law.
The company’s continued success depends on the full and effective utilization of qualified individuals. Therefore, harassment is prohibited and all matters related to recruiting, training, compensation, benefits, promotions and transfers comply with equal opportunity principles and are non-discriminatory.
Cencora is committed to providing reasonable accommodations to individuals with disabilities during the employment process which are consistent with legal requirements. If you wish to request an accommodation while seeking employment, please call 888.692.2272 or email hrsc@cencora.com. We will make accommodation determinations on a request-by-request basis. Messages and emails regarding anything other than accommodations requests will not be returned
