Director, BI & Analytics

SavATree•,

4d•$175,000 - $200,000•Remote

About The Position

SavATree is seeking a Director of Business Intelligence & Analytics to lead the development of a scalable, trusted enterprise reporting and analytics function across a complex, multi-unit services organization. This leader will be responsible for both what we measure and how we deliver it: establishing financially grounded KPIs and analytical frameworks, while designing a BI environment that can effectively serve executives, field leaders and functional teams. The data is largely in place; the work is in combining it into reporting the business can act on. A reporting reset is underway to consolidate conflicting metric definitions into a single governed set that ties to the financials. The SavATree Division is moving to Microsoft Dynamics 365, while the Thrive Division will remain on separate systems. The Director will carry that work forward with significant latitude to shape the function. This is not primarily a data engineering role. The ideal candidate will combine business and financial acumen, analytical rigor, BI architecture and product thinking, and sufficient technical depth to direct technical delivery effectively.

Requirements

8–12+ years of experience across business intelligence, analytics, FP&A or related functions, including leadership responsibility.
Demonstrated experience designing and scaling enterprise BI/reporting environments.
Experience in a multi-unit, multi-location or operationally complex business; field services, home services, route-based services, retail, healthcare services or similar industries preferred.
Strong financial and commercial acumen, including budgeting, forecasting and variance analysis.
Strong SQL and advanced Excel capabilities.
Significant experience with modern BI platforms such as Sigma, Power BI, Tableau or equivalent.
Working knowledge of dimensional modeling, semantic layers, data warehouses, ETL/ELT and data governance.
Hands-on experience with a modern cloud data stack — Snowflake or equivalent warehouse, dbt or comparable transformation tooling, and managed ingestion such as Fivetran.
Exposure to reporting continuity through an ERP or core system migration preferred.
Experience directing technical development teams, internal or contracted.
Strong executive communication and stakeholder-management skills.
Demonstrated curiosity and practical adoption of AI and emerging analytics tools.

Nice To Haves

The ideal candidate combines the analytical orientation of a senior business or FP&A leader with the architecture and product mindset of a strong BI leader.
They should be comfortable: Diagnosing the drivers behind financial and operational performance; Designing reporting environments that scale across hundreds of users; Reviewing SQL and data-model logic with technical teams; Turning ambiguous business questions into specifications an engineer can build from; Reconciling operational KPIs to financial results; Presenting clear, concise conclusions to senior executives and operating leaders.
The strongest candidate will know what the organization should measure, how those measures should fit together, how the reporting environment should be designed, and how to lead the team required to build and improve it.

Responsibilities

Develop and continuously evolve a scalable enterprise BI and reporting architecture across divisions, regions and locations.
Lead the reporting reset — consolidate conflicting metric definitions into one governed set, tie reporting out to financial results, and hold new build to that standard.
Design models and definitions to survive a source-system change and to reconcile across divisions on different ERPs.
Establish consistent executive, regional, branch and functional reporting with clear drill paths from results to underlying drivers.
Build a governed self-service analytics environment that balances accessibility, consistency and data integrity.
Rationalize existing reports and tools, eliminating duplicative or low-value reporting.
Help shape the Company’s BI technology strategy through a structured evaluation of the current Sigma environment against alternative platforms and recommend a go-forward toolset and migration path.
Establish standards for KPI definitions, dashboard development, governance, deployment, access and lifecycle management.
Build an integrated analytical framework connecting operating activity to revenue, profitability and financial performance.
Develop reporting across: Marketing funnel KPIs, including leads, appointments, visits, pitches, sales and conversion; Sold work, cancellations, backlog, scheduling and production; Labor hours, capacity, utilization, routing and revenue per hour; Customer mix, including new, existing, lapsed and reactivated customers; Service, channel and customer mix; Price, volume, mix and timing.
Partner with FP&A to ensure operational reporting is aligned with actuals, budget, forecast and prior year.
Develop pacing and forecasting views incorporating production days, holidays, weekends, seasonality, weather, backlog and year-to-go expectations.
Create diagnostic reporting that helps leaders understand not only what changed, but why and what action is required.
Partner with IT (Enterprise Architecture, Business Applications) to ensure BI solutions align with enterprise architecture, data standards, system integrations, and broader technology strategy. IT owns enterprise architecture, source systems and ingestion; this role owns the analytical models and reporting built on top of them.
Define analytical data models and semantic structures that support consistent reporting across organization, service, customer, channel and time dimensions.
Maintain sufficient technical depth to independently interrogate data, validate business logic, challenge technical solutions, and build directly.
Lead external delivery partners, translating priorities set with Finance and Operations leadership into a disciplined development roadmap.
Serve as the interface between the technical team and business stakeholders, converting business questions into buildable specifications and technical output into something operators can act on.
Establish strong QA, data-quality and deployment practices.
Leverage emerging AI and development tools to improve analytical and development productivity.
Drive adoption through stakeholder engagement, training and continuous improvement.