Data Analyst
About The Position
Join our team at Great Lakes Management as our Data Analyst! Data Analyst Responsibilities: Data Quality, Modeling & AI Readiness Clean, standardize, and validate CRM, financial, and operational data to ensure accuracy and consistency Build and maintain analytics- and AI-ready datasets with well-defined schemas and business logic Identify and resolve data gaps, duplication, and inconsistencies across systems Establish and document data definitions and quality standards Data Analysis & Reporting Write, optimize, and maintain complex SQL queries to transform raw data into analytics-ready datasets Design and maintain DOMO dashboards and reports using BI platforms & similar tools Translate business questions into KPIs, metrics, and analytical outputs Deliver recurring and ad-hoc analysis to leadership and cross-functional teams Business Insights & Collaboration Partner with sales, marketing, finance, and operations to understand analytical needs and AI objectives Surface trends, risks, and opportunities through data-driven insights Communicate findings clearly to technical and non-technical stakeholders Process Improvement & Automation Automate data cleansing, validation, and reporting workflows Reduce manual reporting through efficient SQL, ETL pipelines, and BI tooling Document datasets, transformations, and analytical logic to support scalability Systems & Data Enablement Use CRM, accounting, and operational platforms as primary data sources Collaborate with system owners to improve data capture, structure, and reporting usability Troubleshoot data-related issues with a solutions-oriented mindset Data Analyst Qualifications: Required In-person/hybrid work environment at the Great Lakes Corporate office Bachelor’s degree in Data Analytics, Business Analytics, Information Systems, Computer Science, Business, or a related field (or equivalent practical experience) Deep understanding of SQL, including joins, subqueries, window functions, and query optimization Proven ability to clean, model, and analyze CRM, financial, and operational data Strong ownership of data quality and attention to detail Ability to manage multiple priorities independently Excellent written and verbal communication skills Preferred Hands-on experience with DOMO is a huge plus Experience building scalable, AI-ready datasets Experience with ETL processes, data pipelines, and automation workflows Familiarity with CRM systems (e.g., HubSpot), financial systems, or operational platforms
Requirements
- In-person/hybrid work environment at the Great Lakes Corporate office
- Bachelor’s degree in Data Analytics, Business Analytics, Information Systems, Computer Science, Business, or a related field (or equivalent practical experience)
- Deep understanding of SQL, including joins, subqueries, window functions, and query optimization
- Proven ability to clean, model, and analyze CRM, financial, and operational data
- Strong ownership of data quality and attention to detail
- Ability to manage multiple priorities independently
- Excellent written and verbal communication skills
Nice To Haves
- Hands-on experience with DOMO is a huge plus
- Experience building scalable, AI-ready datasets
- Experience with ETL processes, data pipelines, and automation workflows
- Familiarity with CRM systems (e.g., HubSpot), financial systems, or operational platforms
Responsibilities
- Clean, standardize, and validate CRM, financial, and operational data to ensure accuracy and consistency
- Build and maintain analytics- and AI-ready datasets with well-defined schemas and business logic
- Identify and resolve data gaps, duplication, and inconsistencies across systems
- Establish and document data definitions and quality standards
- Write, optimize, and maintain complex SQL queries to transform raw data into analytics-ready datasets
- Design and maintain DOMO dashboards and reports using BI platforms & similar tools
- Translate business questions into KPIs, metrics, and analytical outputs
- Deliver recurring and ad-hoc analysis to leadership and cross-functional teams
- Partner with sales, marketing, finance, and operations to understand analytical needs and AI objectives
- Surface trends, risks, and opportunities through data-driven insights
- Communicate findings clearly to technical and non-technical stakeholders
- Automate data cleansing, validation, and reporting workflows
- Reduce manual reporting through efficient SQL, ETL pipelines, and BI tooling
- Document datasets, transformations, and analytical logic to support scalability
- Use CRM, accounting, and operational platforms as primary data sources
- Collaborate with system owners to improve data capture, structure, and reporting usability
- Troubleshoot data-related issues with a solutions-oriented mindset
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
