Pay
In line with similar jobs
$103K–$178K against $122K–$190K, the middle half of what similar US postings state.
From 321 postings in the last year. Stated ranges, not salaries paid.
Reads like an Analytics Engineer role: dbt models and clean tables.
Oshkosh, Wisconsin, United States
Live, first seen by us 18 days agoPay Range: $103,300.00 - $177,700.00 The above pay range reflects the minimum and maximum target pay for the position across all U.S. locations. Within this range, individual pay is determined by various factors, including the scope and responsibilities of the role, the candidate's experience, education and skills, as well as the equity of pay among team members in similar positions. Beyond offering a competitive total rewards package, we prioritize a people-first culture and offer various opportunities to support team member growth and success.Read the full posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Build and maintain scalable data transformation pipelines and dimensional models
Standardize business definitions and curate the enterprise semantic layer
Implement software engineering practices such as Git, code reviews, and CI/CD in analytics
Translate business unit reporting needs into robust data models
Optimize analytical query performance and warehouse resource use
Data Modeling Architect, build, and maintain scalable, performant data transformation pipelines and dimensional models
Standardize business definitions and curate the enterprise semantic layer to ensure consistent metric reporting across all business units.
Implement software engineering best practices within analytics: Git version control, modular SQL, code reviews, regression testing, and CI/CD deployment.
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.
Optimize analytical query performance, warehouse resource consumption, and end-user access patterns.
Bachelor’s or master’s degree in computer science, Information Systems, Business Analytics, Mathematics, Engineering, or a related discipline.
SQL: Advanced mastery of complex SQL (window functions, performance tuning, query profiling, dynamic modeling).
Proven ability to translate ambiguous business requirements into robust, production-grade analytical data models.
7+ years of experience in data analytics, business intelligence, or data engineering.
Experience within manufacturing, industrial IoT, supply chain environments.
2+ years of demonstrated leadership experience, including leading technical projects, mentoring analysts, or serving as a team lead.
Education & Experience - 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.
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In line with similar jobs
$103K–$178K against $122K–$190K, the middle half of what similar US postings state.
From 321 postings in the last year. Stated ranges, not salaries paid.
Day 18
Similar jobs usually come down between day 6 and day 47.
From 1,405 similar postings that came down. Coming down is not always a hire.
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- 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
- 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.
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.
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.
- 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).
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.
- 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.
- 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.
- 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).
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We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
At Oshkosh, we build, serve and protect people and communities around the world by designing and manufacturing some of the toughest specialty trucks and access equipment. We employ over 18,000 team members all united by a common purpose. Our engineering and product innovation help keep soldiers and firefighters safe, is critical in building and keeping communities clean and helps people do their jobs every day.
SUMMARY
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
Strategic Leadership & Team Enablement
Stakeholder Collaboration & Product Delivery
QUALIFICATIONS
Education & Experience
Technical Proficiencies
Core Competencies
WHY OSHKOSH?
Moving the future forward is our priority and this includes your future. We encourage professional development and champion our employees’ success through various skills and training opportunities. Named one of the World’s Most Ethical Companies™ by Ethisphere Institute for six consecutive years, everything we do at Oshkosh is guided by our core values and the 15k+ team members around the world who embody them.
We put people first. We do the right thing. We persevere. We are better together.
Pay Range:
$103,300.00 - $177,700.00The above pay range reflects the minimum and maximum target pay for the position across all U.S. locations. Within this range, individual pay is determined by various factors, including the scope and responsibilities of the role, the candidate's experience, education and skills, as well as the equity of pay among team members in similar positions. Beyond offering a competitive total rewards package, we prioritize a people-first culture and offer various opportunities to support team member growth and success.
Oshkosh is committed to working with and offering reasonable accommodation to job applicants with disabilities. If you need assistance or an accommodation due to disability for any part of the employment process, please contact us at corporatetalentacquisition@oshkoshcorp.com.
Oshkosh Corporation is a merit-based Equal Opportunity Employer. Job opportunities are open for application to all qualified individuals and selection decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, or other protected characteristic. To the extent that information is provided or collected regarding categories as provided by law it will in no way affect the decision regarding an employment application.
Oshkosh Corporation will not discharge or in any manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with Oshkosh Corporation's legal duty to furnish information.
Certain positions with Oshkosh Corporation require access to controlled goods and technologies subject to the International Traffic in Arms Regulations or the Export Administration Regulations. Applicants for these positions may need to be "U.S. Persons," as defined in these regulations. Generally, a "U.S. Person" is a U.S. citizen, lawful permanent resident, or an individual who has been admitted as a refugee or granted asylum.
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Pay Range: $103,300.00 - $177,700.00 The above pay range reflects the minimum and maximum target pay for the position across all U.S. locations. Within this range, individual pay is determined by various factors, including the scope and responsibilities of the role, the candidate's experience, education and skills, as well as the equity of pay among team members in similar positions. Beyond offering a competitive total rewards package, we prioritize a people-first culture and offer various opportunities to support team member growth and success.
Oshkosh, Wisconsin, United States
Working pattern and location restrictions need checking in the full posting.
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