Head of Enterprise Analytics & Decision Systems (Remote)

your Jared

Northern (KY)

Hybrid

USD 140,000 - 190,000

Full time

7 days ago

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Benefits offered by this job

Fully Remote Position

Competitive Pay

Comprehensive Benefits Package

Career Development

Cutting-Edge Projects

Positive Work Environment & Company •

Job summary

Bollinger Shipyards is seeking a Senior Manager Analytics & Decision Systems to lead analytics program development across Finance, Operations, Engineering, Supply Chain, and Business Development. You will drive KPI frameworks and executive dashboards to support informed decision-making.

Role requires 8+ years in analytics, leadership experience, and strong Power BI expertise. This position is fully remote and partners with IT and leadership to align analytics with strategic priorities.

Qualifications

Bachelor’s degree in Information Systems, Analytics, Business, Engineering, Computer Science or related field.
8+ years of experience in analytics, business intelligence, reporting.
3+ years of leadership experience.
Proven experience building enterprise analytics programs, KPI frameworks, and reporting capabilities.
Strong experience with Power BI or similar enterprise BI platforms.

Responsibilities

Define and lead the enterprise analytics and reporting strategy.
Establish and standardize enterprise KPI frameworks across Finance, Operations, Engineering, Supply Chain, and Business Development.
Lead delivery and ongoing enhancement of enterprise executive dashboards and decision-support tools.
Oversee development of Power BI dashboards, semantic models, and self-service reporting capabilities.
Ensure consistency, accuracy, and alignment of operational and financial reporting across the enterprise.
Partner with Data Engineering and Enterprise Architecture teams to ensure reliable, governed, and accessible data.
Drive adoption of analytics tools and data-driven decision-making practices across the organization.
Establish reporting governance, dashboard standards, and analytics development methodologies.
Prioritize analytics initiatives aligned to business value and operational impact.
Lead and develop analytics engineering and BI resources.
Partner with business leaders to identify opportunities for operational improvement through analytics and insight generation.
Monitor analytics adoption, usage, and effectiveness to ensure measurable business value.