Analytics Manager

Summary: As the Analytics Manager, you lead the charge in delivering impactful business intelligence and predictive analytics solutions by partnering closely with stakeholders to define priorities and turn business needs into technical solutions. As the product owner for analytics initiatives, you’ll guide the strategic vision while staying hands-on with execution, ensuring the development of dashboards, reports, data pipelines, and models that fuel smart, data-driven decisions across the organization. This is a collaborative leadership role that blends curiosity, clarity, and a drive to build tools that truly make a difference.

Essential Duties: Essential job duties for this position include the following items. Other duties must be performed as assigned or required.

Lead the Analytics Vision: Turn business goals into a focused analytics strategy, prioritizing work that delivers measurable impact. Own and manage the analytics backlog, balancing quick wins with long-term priorities that move the organization forward.

Oversee Insightful Solutions: Guide the development of dashboards, reports, and data models using tools like Tableau, Power BI, Databricks, AWS, Azure and work with languages like Python and SQL. Ensure delivery of scalable, user-friendly solutions that support operational excellence and executive decision-making while limiting long-term tech debt.

Shape Strategic Direction: Identify key opportunities to improve performance and efficiency through advanced analytics and modeling. Develop business cases that influence organizational priorities and investments.

Collaborate & Influence: Partner with engineering, operations, and executive leadership to strengthen how we organize, connect, and use our data. Serve as a thought leader in analytics by turning complex data into meaningful stories that drive action and inspire change.

Lead & Develop Talent: Manage and mentor a team while fostering a culture of curiosity, innovation, and accountability. Help others across the organization feel more confident using data by guiding them in how to understand, explore, and apply insights in their day-to-day decisions.

Enhance Stakeholder Engagement: Actively gather feedback, track usage of analytics tools, and refine solutions to meet evolving business needs. Build trust by delivering meaningful insights and staying engaged through regular operational reviews.

Demonstrate HODGE Values: Model core values of Family, Integrity, Ambition, Respect, and Balance. Uphold, support, and promote all company policies and procedures. Remember that success comes from treating people like family.

Qualifications: To perform this job successfully, the Analytics Manager must be able to perform each essential duty satisfactorily. The following requirements are representative of the minimum knowledge, skill, and ability required.

Education/Experience:

Required:

5+ years of experience in analytics, business intelligence, or data engineering roles.

Hands-on experience with BI tools (e.g., Power BI and Tableau) and analytics platforms (e.g., Databricks).

Strong communication and stakeholder management skills, able to translate business needs into technical requirements.

Demonstrated experience in driving business optimization through analytics.

Proven track record of working closely with stakeholders to define analytics requirements and deliver solutions that drive business impact.

Experience with data-driven decision-making and developing predictive or descriptive analytics models.

Bachelor’s degree in data science, business analytics, computer science, statistics, engineering, or a similar discipline.

Preferred:

Experience with programming languages Python, R, or similar languages used for data engineering, statistical analysis and modeling.

Familiarity with cloud environments (AWS, Azure, or GCP) and building or managing data pipelines.

Experience applying Agile project management or Scrum framework, including leading cross-functional work or acting as a Product Owner.

Background in warehouses, supply chain, or manufacturing environments where data supports operational performance.

Master’s degree in data science, analytics, business administration, or a related field.

Exposure to machine learning or predictive modeling is a plus.