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. 

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.