Manager, Data & Intelligence (Remote)

Great Day Improvements: A Family of Brands•Twinsburg, OH

4h•$140,000 - $150,000•Remote

About The Position

Great Day Improvements - Manager, Data & Intelligence (Remote, USA) Company Overview Since its founding 13 years ago, Great Day Improvements, LLC has grown rapidly toward its vision of becoming one of the largest home improvement companies in the U.S. Headquartered in Twinsburg, Ohio, Great Day Improvements is a $1.5 billion, vertically integrated, direct-to-consumer provider of premium home improvement products. The company’s family of brands includes Patio Enclosures®, Champion Windows and Home Exteriors®, Universal Windows Direct®, Apex Energy Solutions®, Stanek Windows®, Leafguard®, Englert®, and The Bath Authority. With an expanding workforce of over 4,800 employees across 130 metropolitan markets throughout the U.S., Great Day Improvements continues to rank among the top home improvement companies nationwide and is one of the fastest growing private companies in America. Summary The Manager, Data & Intelligence is a hands-on leadership role responsible for overseeing both the Business Intelligence (BI) and Data Engineering teams. Reporting to the Director, Data & Intelligence, this role serves as a critical force multiplier, driving BI modernization, supporting data engineering workstreams tied to AI initiatives, and providing day-to-day people management across a mid-sized team of 6 to 10 analysts and engineers. A central focus of this role is leading the transition to a Databricks Apps-forward BI platform, where AI-assisted programming accelerates the development of high-quality, self-service dashboards. The ideal candidate will bring deep marketing domain expertise, ideally honed at a Big 4 consulting firm, and the ability to translate complex marketing analytics needs into scalable, governed BI solutions. This person will also serve on the company’s Data Governance panel and act as the primary point of contact for business stakeholders on BI-related initiatives, balancing strategic thinking with operational execution. Salary Range: $140,000 - 150,000 This salary range represents a good faith estimate of the compensation for this position. Actual compensation may vary based on education, experience, knowledge, skills, abilities, internal equity, and alignment with market data

Requirements

Bachelor’s degree in Business Analytics, Data Science, Information Systems, Marketing Analytics, or a related field
7+ years of progressive experience in Business Intelligence, Data Analytics, Data Engineering, or a related discipline
3+ years of direct people management experience, including hiring, performance management, and team development
Strong marketing domain knowledge, including familiarity with marketing KPIs, attribution modeling, campaign analytics, and customer lifecycle metrics
Hands-on experience with modern BI platforms (Databricks, Tableau, Power BI) including administration, governance, and dashboard development
Solid understanding of data engineering concepts: ELT/ETL pipelines, data modeling, SQL, and cloud data platforms
Proven track record of managing complex, cross-functional analytics projects with multiple competing stakeholder priorities
Excellent interpersonal, presentation, and communication skills with the ability to influence at the executive level

Nice To Haves

Consulting background at a Big 4 firm (Deloitte, EY, PwC, KPMG) or equivalent management consulting experience with a focus on data & analytics or marketing transformation
Experience with Databricks (including Databricks SQL, Unity Catalog, and/or Databricks Apps)
Familiarity with AI-assisted development tools and their application to BI and data engineering workflows
Experience managing BI environments across multiple brands or business units
Exposure to Azure data technologies (Azure Data Lake, Azure DevOps, Databricks on Azure)
Experience working in a direct-to-consumer, home services, or marketing-intensive industry
Experience participating in or establishing data governance programs

Responsibilities

Lead the migration from legacy BI tools (Tableau Cloud, Power BI) to a Databricks Apps-centered platform for dashboard development and analytics delivery
Champion AI-assisted development practices within the BI team, enabling faster iteration, higher-quality output, and reduced time-to-insight
Define standards for dashboard design, data visualization, and semantic layer governance within the Databricks ecosystem
Evaluate and integrate emerging AI-assisted development tools and workflows to continuously improve BI delivery speed and quality
Directly manage, mentor, and develop a team of 6 to 10 data analysts and data engineers supporting multiple business units
Set clear priorities, assign projects, conduct performance reviews, and foster a collaborative, growth-oriented team culture
Serve as a working manager, willing to build dashboards, write queries, and troubleshoot alongside the team when needed
Identify skill gaps and drive professional development plans, particularly around Databricks, AI-assisted tooling, and modern data engineering practices
Oversee the data engineering team’s workstreams, ensuring data pipelines, ingestion processes, and transformations are reliable, performant, and well-documented
Coordinate data engineering tasks related to the company’s AI initiatives, partnering with the Director to prioritize and sequence work effectively
Ensure data engineering deliverables meet quality, security, and governance standards required by downstream BI and AI consumers
Serve as the primary liaison between business stakeholders and the Data & Intelligence team for all BI initiatives
Lead regular stakeholder meetings to intake requests, prioritize the backlog, align on reporting goals, and manage competing demands
Bring strong marketing domain knowledge to the role, translating marketing KPIs, attribution models, and campaign performance needs into actionable BI solutions
Communicate complex data insights and project updates clearly and persuasively to both technical and non-technical audiences, including executive leadership
Sit on the company’s Data Governance panel, contributing to policies around data quality, metadata management, data classification, and access controls
Establish and enforce BI-specific governance standards including report certification, naming conventions, and semantic layer definitions
Collaborate with data engineering and IT to ensure governance frameworks are operationalized across the analytics ecosystem