Come be DISRUPTIVE with us! At Milwaukee Tool we firmly believe that our People and our Culture are the secrets to our success -- so we give you unlimited access to everything you need to create innovative new solutions on our engineering team. As a Sr. Data Engineer, you will design, build, and support scalable data solutions that enable faster, more reliable decision-making across engineering, test lab, and product development operations. You will partner with cross-functional teams to transform raw data into trusted, governed, analytics-ready data products through modern data pipelines, cloud platforms, data modeling, and data quality practices.

You must be permanently eligible to work in the U.S. without sponsorship for this position.

Duties and Responsibilities 

• aDesign, develop, and maintain scalable data pipelines, data models, and data integration solutions that support engineering and test operations. 

• Build reliable ETL/ELT processes to ingest, transform, validate, and deliver data from multiple source systems into analytics-ready environments. 

• Partner with engineering, lab operations, IT, analytics, and business stakeholders to understand data needs and translate them into technical solutions. 

• Establish and maintain data quality checks, validation rules, and monitoring processes to ensure trusted and accurate data. 

• Develop and optimize data warehouses, data lakes, and cloud-based data platforms for performance, reliability, and scalability. 

• Create reusable data assets, curated datasets, and documentation that enable self-service reporting, analytics, and operational visibility. 

• Collaborate with software developers and IT teams on secure data architecture, system integrations, source control, deployment, and development best practices. 

• Translate business strategy and operational needs into technical data solutions that improve efficiency, quality, and speed of decision-making. 

• Monitor pipeline performance, troubleshoot production issues, and proactively improve data reliability, observability, and maintainability. 

• Mentor team members on data engineering standards, coding practices, documentation, and data governance principles. 

• Adhere to timelines and excel in a fast-paced, high-energy environment while balancing technical excellence with practical business impact. 

Qualifications 

• Bachelor’s degree in Computer Science, Computer Engineering, Data Engineering, Information Systems, or a related technical field; equivalent experience may be considered. 

• 5+ years of experience in data engineering, software engineering, analytics engineering, or related technical roles. 

• Strong proficiency in SQL and at least one programming language such as Python, C#, Java, or Scala. 

• Experience designing and supporting ETL/ELT pipelines, data warehouses, data lakes, relational databases, and cloud-based data platforms. 

• Experience working in cloud environments such as Azure or AWS, including data storage, compute, orchestration, and security concepts. 

• Working knowledge of data modeling, database design, data integration patterns, APIs, and scalable system architecture. 

• Familiarity with modern data engineering tools and practices such as Spark, Databricks, Airflow, dbt, Fabric, or automated testing. 

• Strong understanding of data quality, data governance, data security, documentation, and operational monitoring practices. 

• Ability to understand complex business processes, create process maps, and translate operational workflows into data solutions. 

• Strong analytical, problem-solving, and communication skills with the ability to influence technical decisions across cross-functional teams.