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# Data Analyst Lead

- **Company:** JLG Industries, Inc. i
- **Location:** Oshkosh, WI, United States
- **Experience:** Expert
- **Salary:** $103,300.0 - $177,700.0
- **Contract:** Permanent contract
- **Skills:** Query Performance, Application Programming Interfaces (APIs), Business Intelligence Development, BigQuery, Command-Line Interface, Cloud Computing, Cloud Database, Profiling, Code Review, Information Systems, Continuous Integration, Information Engineering, Data Governance, Data Transformation, Data Visualization, DevOps, Dimensional Modeling, Github, Python (Programming Language), Performance Tuning, Raw Data, Role-Based Access Control, Regression Testing, Power BI, Software Engineering, SQL Databases, Scripting, Sql Optimization, Git, Information Technology, Data Analytics, Star Schema, Data Management, Tools for Reporting, Azure Synapse Analytics, Software Version Control, Databricks
- **Published:** October 17, 2026
- **Apply:** https://oshkoshcorporation.wd5.myworkdayjobs.com/Oshkosh/job/Oshkosh-Wisconsin-United-States/Data-Analyst-Lead_R50810

## About the Role

* Bachelor's or master's degree in computer science, Information Systems, Business Analytics, Mathematics, Engineering, or a related discipline.
 * 7+ years of experience in data analytics, business intelligence, or data engineering.
 * 2+ years of demonstrated leadership experience, including leading technical projects, mentoring analysts, or serving as a team lead.

Technical Proficiencies

 * SQL: Advanced mastery of complex SQL (window functions, performance tuning, query profiling, dynamic modeling).
 * Cloud Platforms & Warehousing: Hands-on experience with modern cloud data platforms such as Databricks, or Azure Synapse / BigQuery.
 * Version Control & DevOps: Proficiency with Git/GitHub, CI/CD pipelines, and command-line interfaces (CLI).
 * Business Intelligence: Advanced data visualization and data modeling experience with Power BI etc.
 * Modern Transformation & Modeling: Expertise with dbt and Kimball dimensional modeling techniques (Star/Snowflake schemas etc).
 * Scripting: Working proficiency in Python for lightweight data scripting, API ingestion, or automation.

Core Competencies

 * Proven ability to translate ambiguous business requirements into robust, production-grade analytical data models.
 * Exceptional communication and storytelling skills, with the ability to convey technical architectures to business executives and business context to engineers.
 * Strong product mindset and empathy for end-user analytics workflows.
 * Experience within manufacturing, industrial IoT, supply chain environments.

## Description

The Data Analyst Lead sits at the intersection of business intelligence, data engineering, and domain analytics. This role is responsible for elevating our analytics maturity by extracting measurable business value from data-transforming complex enterprise, supply chain, and manufacturing data into high-impact, decision-ready analytical assets that directly drive operational efficiency, cost reduction, and top-line growth. You will partner closely with business stakeholders across the enterprise to turn strategic business questions into scalable, high-value data products.

YOUR IMPACT

Data Modeling

 * Architect, build, and maintain scalable, performant data transformation pipelines and dimensional models using cloud data warehouses/lakehouses/dbt.
 * Implement software engineering best practices within analytics: Git version control, modular SQL, code reviews, regression testing, and CI/CD deployment.
 * Standardize business definitions and curate the enterprise semantic layer to ensure consistent metric reporting across all business units.
 * Optimize analytical query performance, warehouse resource consumption, and end-user access patterns.

Strategic Leadership & Team Enablement

 * Lead modern analytics engineering practices, advanced SQL techniques, and data modeling frameworks.
 * Act as the technical liaison between upstream Data Engineering teams (responsible for raw data ingestion and infrastructure) and downstream business stakeholders.
 * Establish data documentation standards, lineage tracking across projects.

Stakeholder Collaboration & Product Delivery

 * Partner directly with business unit leaders (e.g., Supply Chain, Manufacturing Operations, Lifecycle services) to understand operational reporting requirements and translate them into robust data models.
 * Partner with data scientists and BI developers to design intuitive, high-performance dashboards, self-service datasets, and reporting frameworks in tools like Power BI.
 * Enforce data governance, role-based access controls (RBAC), and compliance policies across reporting datasets.