Senior Data Engineer: Scale Data Pipelines & Analytics

Milwaukee Tool; Town of Montana (WI); On-site; USD 120,000 - 160,000; Full time

Job summary

Milwaukee Tool is seeking a Sr. Data Engineer to design, build, and support scalable data solutions that enable faster decision‑making across engineering, test lab, and product development operations.

You will partner with cross‑functional teams to transform raw data into analytics‑ready data products through modern data pipelines, cloud platforms, data modeling, and data quality practices, while mentoring teammates and upholding governance in a fast‑paced environment.

Qualifications

• Bachelor's degree in a technical field or equivalent experience.
• 5+ years in data engineering or related roles.
• Strong SQL and at least one major programming language.
• Experience with ETL/ELT, data warehouses, data lakes, and cloud platforms.
• Experience with Azure or AWS cloud environments and security concepts.
• Knowledge of data modeling, APIs, and scalable architectures.
• Familiarity with data governance, quality, and observability practices.

Responsibilities

• Design, develop, and maintain scalable data pipelines and data models for engineering and test operations.
• Build reliable ETL/ELT processes for analytics-ready data assets.
• Collaborate with cross-functional teams to translate data needs into solutions.
• Establish data quality checks and monitoring for trusted data.
• Develop and optimize cloud-based data platforms for performance and reliability.
• Create reusable data assets and documentation for self-service reporting.

Skills

SQL

Python

C#

Java

Scala

Education

Bachelor's degree in Computer Science or related field

Tools

Spark

Databricks

Airflow

DBT

Fabric

Job description

Milwaukee Tool is seeking a Sr. Data Engineer to design, build, and support scalable data solutions that enable faster decision‑making across engineering, test lab, and product development operations.

You will partner with cross‑functional teams to transform raw data into analytics‑ready data products through modern data pipelines, cloud platforms, data modeling, and data quality practices, while mentoring teammates and upholding governance in a fast‑paced environment.