Data Analytics Manager

American Elevator Group (AEG) is the largest independent elevator service company in North America, consisting of a collection of well-established elevator service companies operating throughout the United States. Backed by Arcline Investment Management, AEG has a significant footprint in the elevator industry and is rapidly growing. We are looking for an experienced Data Analytics Manager to help us continue streamlining and maintaining business intelligence.
 

The Data Analytics Manager will play a pivotal role and work directly with management to advance organizational performance by leveraging data analytics to provide valuable tools and insight to the business.  This role requires expertise in data analytics, ERP systems, creating and tracking key performance indicators (KPIs), and utilizing Power BI to transform raw data into valuable insights for departmental decision-making.  You will oversee data collection, processing, modeling, and analysis to ensure accuracy and consistent reporting for management.  
 

Responsibilities:

• Analyze complex datasets using data analysis techniques and tools to identify trends, patterns, and actionable insights.
• Conduct ad-hoc analyses to support strategic initiatives and operational/financial strategies.
• Translate findings into clear reports, dashboards, and presentations to drive data-driven decisions.
• Design, develop, and maintain KPI dashboards (e.g., Power BI) for real-time performance monitoring.
• Build automated reporting systems and data visualizations to communicate insights across departments.
• Oversee report requests, ensuring prioritization, accuracy, and alignment with business goals.
• Partner with stakeholders to define analytics needs, metrics, and business objectives.
• Align data strategies with organizational goals, including revenue/sales data management and ERP system integration.
• Ensure data integrity through robust validation, cleaning, and testing.
• Develop departmental standards for data collection, processing, and reporting.
• Evaluate and optimize internal systems for efficiency and accuracy.
• Design and implement scalable analytics frameworks by leveraging data warehouses, cloud platforms and automation tools.
• Configure and maintain analytics solutions, transforming raw data into actionable insights.
• Monitor industry trends and emerging technologies to enhance analytics practices.
• Innovate systems to simplify complex problems and improve decision-making frameworks.
• Performs other duties as assigned.

Work Environment & Hazards:

• This position is fully remote, but may be requested seldomly to travel to a business unit location.
   

Special Physical Demands:

• Prolonged periods of sitting at a desk and working on a computer.
• Must be able to lift 15 pounds at times.
   

Work Contact Group:

• Contact with operations and leadership teams, Finance/Sales departments, and senior leadership.
• ERP/Power BI vendors, third-party data providers.

• Bachelor’s degree in Data Science, Computer Science, Statistics, Business Administration, or a related quantitative field.
• 5+ years in data analytics or related roles, including hands-on expertise in Data mining, modeling, statistical analysis, ERP systems, and Power BI dashboard development.
• Advanced skills in SQL, data visualization tools (Power BI, Tableau), and Excel.
• Experience with data infrastructures and cloud-based platforms (AWS, Azure, GCP) for data integration and warehousing.
• Proven ability to understand, navigate, and query complex databases and automated reporting systems.
• Ability to extract and synthesize data from on-premises/cloud sources to identify trends and forecasts.
• Strong ability to interpret complex datasets and translate findings into actionable business recommendations.
• Excellent verbal/written communication skills to convey technical concepts to non-technical audiences.
• Track record of collaborating with teams (finance, sales, operations) to align analytics with business goals.
• Ability to manage multiple projects and processes simultaneously while ensuring data accuracy and compliance.