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Director, Data & Analytics LOCATION: Corporate Headquarters Johnstown, CO (Position is hybrid but ... Experience with Microsoft Foundry, OneLake, Azure ML Studio and similar machine learning platforms.
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Director, Data & Analytics LOCATION: Corporate Headquarters - Johnstown, CO (Position is hybrid but ... Experience with Microsoft Foundry, OneLake, Azure ML Studio and similar machine learning platforms.
Director, Data & Analytics
Johnstown, CO · On-site
Director, Data & Analytics LOCATION: Corporate Headquarters - Johnstown, CO (Position is hybrid but ... Experience with Microsoft Foundry, OneLake, Azure ML Studio and similar machine learning platforms.
Director, Data & Analytics LOCATION: Corporate Headquarters - Johnstown, CO (Position is hybrid but ... Experience with Microsoft Foundry, OneLake, Azure ML Studio and similar machine learning platforms.
Quick apply
Director, Data & Analytics LOCATION: Corporate Headquarters - Johnstown, CO (Position is hybrid but ... Experience with Microsoft Foundry, OneLake, Azure ML Studio and similar machine learning platforms.
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Director Data Analyst Machine Learning information
What is the difference between Director Data Analyst Machine Learning vs Data Scientist?
| Aspect | Director Data Analyst Machine Learning | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's or Master's in Data Science, Computer Science, or related fields; experience in machine learning | Bachelor's or Master's in Data Science, Statistics, Computer Science; strong programming skills |
| Work Environment | Leads teams, manages projects, strategic planning | Hands-on data analysis, model development, experimentation |
| Employer & Industry Usage | Tech companies, finance, healthcare, retail | Research institutions, tech firms, consulting |
The main difference is that the Director Data Analyst Machine Learning oversees teams and strategic initiatives, while Data Scientists focus on developing models and analyzing data directly. The director role emphasizes leadership and project management, whereas data scientists are more hands-on with technical tasks.
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Job description
JOB TITLE: Director, Data & Analytics
LOCATION: Corporate Headquarters Johnstown, CO
(Position is hybrid but must be commutable/accessible to corporate headquarters in Northern Colorado.)
REPORTS TO: Vice President, Information Technology
FLSA STATUS: Salaried, Non-Exempt
FUNCTION: Responsible for the technical leadership, delivery oversight, prioritization, and operational maturity of the companys data warehouse, pipelines, semantic models/cubes, and data experience layers.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Other duties may be assigned.
Leadership and Team Management
Lead, coach, and develop the Data & Analytics team, including developers and related technical resources.
Provide clear direction, work planning, prioritization, and performance management for the team.
Establish team standards, operating rhythms, delivery practices, and documentation expectations.
Serve as escalation point and technical backstop for warehouse, pipeline, model/cube, and reporting work.
Build cross-training and redundancy so function is sustainable and not dependent on any one individual.
Data & Analytics Strategy and Delivery
Own the delivery and support of enterprise data and analytics solutions, including:
data warehouse architecture and administration
data integration and pipelines
semantic models and cubes
enterprise reporting and dashboards
Guide solution design to ensure data products are scalable, secure, maintainable, and business-aligned.
Oversee the intake, assessment, prioritization, and execution of analytics initiatives.
Maintain a roadmap for data and analytics capabilities that supports operational, financial, risk, HR, environmental, and executive reporting needs.
Ensure analytics delivery is treated as an enterprise capability serving the whole business, rather than a narrow sub-function of IT or any single department.
Technical Leadership
Provide technical oversight and practical guidance in:
enterprise data warehousing
ETL/ELT and data pipeline design
dimensional modeling and semantic layer design
cubes and analytical data structures
Power BI datasets, reports, dashboards, governance, and performance tuning
Review architecture and design decisions to promote reliability, usability, scalability, and supportability.
Partner closely with Software Development to define, obtain, and improve operational data sources needed for analytics solutions.
Work with IT leadership to establish standards for data quality, metadata, naming, lineage, security, and lifecycle management.
Support troubleshooting and continuity of delivery by being capable of guiding, reviewing, and backing up the teams technical work when needed.
Business Engagement and Relationship Management
Translate business goals into practical data and analytics solutions.
Partner with stakeholders across the company to clarify needs, define requirements, and manage expectations.
Serve as a primary liaison between technical teams and business partners for enterprise reporting and analytics initiatives.
Help stakeholders understand priorities, tradeoffs, dependencies, and delivery timelines.
Project Management, Analysis, and Quality
Apply strong project management discipline to analytics initiatives, including planning, scope definition, milestone tracking, issue management, and status communication.
Perform or oversee business analysis activities such as requirements gathering, process review, use-case development, and solution validation.
Establish and enforce QA practices for data and analytics solutions, including testing strategy, reconciliation, validation, user acceptance support, and release readiness.
Promote high-quality outputs by ensuring reports, models, and pipelines are accurate, understandable, and fit for business use.
Advanced Analytics, AI, and Enablement
Support the companys use of Microsoft Fabric, Foundry, Azure ML Studio, and advanced analytics tools.
Assist power users in applying machine learning, AI, and automation in practical business scenarios.
Enable and support technical power users across the company in their effective and responsible use of analytics, AI, and self-service tools.
Help define appropriate governance, support boundaries, and best practices for business-facing analytical and AI capabilities.
QUALIFICATIONS:
Required Education and Experience
Bachelors degree in Computer Science, Data Analytics, or a related technical field, or equivalent combination of education and experience.
Strong (5+ years) experience in data warehousing, analytics, business intelligence, and related IT disciplines.
Strong (5+ years) experience managing technical teams, leads, and major cross-functional initiatives.
Demonstrated experience delivering enterprise data and analytics solutions in a complex environment.
Required Technical Knowledge and Skills
Strong working knowledge of:
data warehousing concepts and platforms
data integration, ETL/ELT, and pipeline orchestration
dimensional modeling and semantic modeling
cubes and analytical structures
Dataset design, report development, and performance optimization
Ability to review technical designs, guide architecture decisions, and coach developers on best practices.
Strong understanding of data quality, data governance, security, and supportability considerations.
Experience working with operational system data and partnering with software development teams.
Required Professional Skills
Strong project management skills, including planning, prioritization, coordination, and delivery oversight.
Strong business analysis skills, including requirements elicitation, process understanding, and solution definition.
Strong QA mindset with experience in validation, testing, and release quality.
Excellent verbal and written communication skills with the ability to work effectively with both technical and business audiences.
Ability to build trust, influence decisions, and navigate dependencies across functions.
Strong problem-solving ability, sound judgment, and attention to detail.
Preferred Qualifications
Experience with Microsoft Foundry, OneLake, Azure ML Studio and similar machine learning platforms.
Experience supporting AI-enabled solutions, self-service analytics, or enterprise data enablement.
Experience with large-scale, industrial, operations-heavy, multi-site production animal agricultural.
Familiarity with change management and user enablement for analytics adoption.
Key Competencies
Technical leadership
Team leadership and coaching
Enterprise thinking
Cross-functional collaboration
Business partnership
Project execution
Analytical problem solving
Quality orientation
Communication and influence
Continuous improvement
Success Measures
a stable, well-led Data & Analytics function with clear priorities and accountability
improved alignment between analytics delivery and business needs
reliable and scalable warehouse, pipeline, model, cube, and Power BI solutions
effective partnership with IT leadership, business stakeholders, and power users/analysts
stronger quality, documentation, and support practices
increased organizational capability in analytics, AI, and power-user enablement
PHYSICAL DEMANDS:
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Office work will include, but are not limited to: Reaching, bending and sitting for a prolonged period of time at a work station or desk operating and viewing systems, documents, and calculator. On occasion moving and carrying boxes for storage.
Apply Today!
About Five Rivers Cattle Feeding
Sourced by ZipRecruiter
Industry
Food and drink manufacturing
Company size
501 - 1,000 Employees
Headquarters location
Johnstown, CO, US
Year founded
2005