Data & Analytics Lead - IT
Wayne-sanderson Farms
Oakwood, United States of America
yesterday
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
SeniorJob location
Oakwood, United States of America
Tech stack
Information Systems
Continuous Integration
Data Validation
Data Governance
Data Warehousing
Decision Support Systems
Python
Machine Learning
Power BI
Cloud Services
Standard Sql
Tableau
Cloud Platform System
Data Ingestion
Snowflake
Data Strategy
GIT
Information Technology
Data Analytics
Tools for Reporting
Looker Analytics
Software Version Control
Databricks
Job description
Job Summary: The IT Data & Analytics Lead will help build a new centralized analytics function. This role blends business ownership with technical expertise, owning analytics outcomes while designing scalable data models. You'll shape strategy, partner with stakeholders, and establish trusted data practices that drive meaningful metrics and business decisions., Analytics Strategy & Business Ownership
- Strong business acumen and ability to partner with business stakeholders and leadership to define key metrics, KPIs, and success measures
- Translate business problems into prioritized analytics initiatives and analytics outcomes
- Own and maintain the analytics roadmap, backlog, and prioritization of projects
- Communicate insights, tradeoffs, and data changes to senior stakeholders
- Establish and maintain a shared understanding of metrics, data standards, and ownership across the organization
Analytics Engineering & Technical Leadership
- Provide guidance and leadership to consultants during the implementation of the cloud data platform and development of analytics capabilities
- Support the design and building of analytics ready data models and datasets
- Establish best practices for data modeling, metric definitions, and dataset design
- Review and contribute to analytics engineering code with a focus on correctness, performance, and maintainability
- Experience with BI and reporting tools (Tableau, Power BI, Looker, etc.)
- Define and enforce metric definitions and analytic standards
- Implement data quality checks, validation tests, and monitoring
- Implement data quality checks, validation tests, and monitoring
Enablement & Scale
- Make self service analytics easier and safer for analysts and business users
- Promote data literacy and drive adoption of data-driven decision making across the organization
- Define and implement the analytics intake, prioritization, and delivery process
- Establish best practices to ensure consistency and trust in data, analytics, and reporting
- Establish standards for analytics development, testing, deployment, and documentation
- Create and maintain clear documentation of data sources, transformations, definitions, and logic, * Duties include a typical office setting including extensive computer work, sitting or standing.
- Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
- Must adhere to the company's Code of Conduct and all other policies.
Safety Requirements:
- Follows all departmental and company safety policies and programs.
Requirements
Do you have experience in Stakeholder relationship building?, Do you have a Bachelor's degree?, * 10+ years in relevant work experience
- 5+ years in analytics, BI, or analytics engineering roles
- Experience with cloud data platforms (Snowflake, Databricks, Fabric, etc.)
- Strong SQL and data modeling experience
- Familiarity with BI tools (Tableau, Power BI, Looker)
- Experience working in early-stage or building-from-scratch environments preferred
- Strong communication and stakeholder management skills
Knowledge, Skills and Abilities:
- Experience working in early-stage or building-from-scratch environments
- Familiarity with data ingestion tools (Fivetran, Airbyte, etc.) preferred
- Exposure to version control (Git) and CI/CD practices
- Experience with statistical modeling, predictive analytics, and machine learning to support advanced analytics initiatives
- Understanding of data warehousing concepts (fact/dimension models, etc.)
- Basic Python (nice to have, not required)
- Ability to translate ambiguous questions into structured analytics, * Bachelor's degree in Computer Science, Data Science, Information Systems, or related field; Master's degree preferred.