> Markdown version of [/jobs/ext/4321520-data-analyst](https://www.wearedevelopers.com/jobs/ext/4321520-data-analyst). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Analyst - **Company:** MCKINLEY GROUP INC - **Location:** Minneapolis, MN, United States - **Experience:** Experienced - **Salary:** $95,000.0 - $125,000.0 - **Contract:** Contract - **Skills:** Microsoft Excel, Artificial Intelligence, Data Analysis, Big Data, Spreadsheets, Databases, Data Cleansing, Database Queries, Excel Formulas, Pivot Tables, Power BI, SQL Databases, Tableau (Software), Cloud Platform System, Data Ingestion, GitHub Copilot, Claude Code, Snowflake, Information Technology, Data Analytics, Data Management, GPT - **Published:** October 31, 2026 - **Apply:** https://www.versique.com/opening/data-analyst-48495/ ## About the Role Are you someone who enjoys digging into data, can efficiently move information from spreadsheets and PDFs into structured datasets, is comfortable writing SQL and embraces AI tools to improve accuracy, speed, and productivity? This is a rare opportunity to join a successful investment firm in a highly visible role. You will influence how they leverage data to drive business performance, streamline processes, improve data accessibility, advance analytics capabilities and guide the responsible use of AI technologies., We are seeking a highly analytical Data Analyst with 4-6 years of experience transforming complex data into actionable business insights. The Data Analyst will extract and validate data from Excel files, PDFs, and internal systems, leverage technologies such as SQL and Snowflake to clean and structure data and utilize AI tools like Claude Code to accelerate data preparation, analysis, and reporting. The ideal candidate is equally comfortable writing complex queries, automating processes, and partnering with business stakeholders to solve problems through data., * 4-6 years of experience in data analytics, business intelligence, reporting, or a related field. * Advanced Excel skills including complex formulas, lookups, PivotTables, and large dataset management. * Strong SQL skills with experience developing queries, transformations, and analytical datasets. * Hands-on experience with Snowflake or similar cloud-based data platforms. * Proven ability to clean, integrate, and analyze data from disparate sources, including Excel files, PDFs, and structured databases. * Experience using AI-assisted tools such as Claude Code, ChatGPT, GitHub Copilot, or similar technologies to improve productivity and automate data-related tasks. * Experience creating dashboards and visualizations using Power BI, Tableau, or similar BI tools. * Strong analytical thinking, attention to detail, and problem-solving skills. * Excellent communication skills with the ability to present findings to both technical and non-technical audiences. Ideal Candidate Someone who enjoys digging into messy data, can efficiently move information from spreadsheets and PDFs into structured datasets, is comfortable writing SQL, and embraces AI tools to improve accuracy, speed, and productivity. ## Description * Extract, organize, and validate data from Excel spreadsheets, PDF documents, databases, and third-party systems. * Clean, standardize, transform, and aggregate complex datasets from multiple sources to ensure accuracy and consistency. * Develop and optimize SQL queries, data models, and datasets within related data platforms. * Leverage Claude Code and other AI-enabled tools to streamline data ingestion, transformation, documentation, and reporting workflows. * Analyze large datasets to identify trends, exceptions, risks, and opportunities that support business decision-making. * Create and maintain recurring reports, dashboards, and visualizations for operational and executive stakeholders. * Partner with business teams to gather requirements, define metrics, and deliver meaningful analytical solutions. * Identify opportunities to automate manual reporting and data preparation processes. * Support data quality, governance, and documentation efforts to improve trust and usability of business data.