Milwaukee Tool is looking to solve advanced analytical needs and improve efficiency, performance, and reliability of their data infrastructure
Requirements
- Enterprise data management
- Cloud infrastructure and data processing on Microsoft Azure
- Designing, building, and optimizing Azure data pipelines
- Azure data components (ADLS, ADF, Databricks, Synapse, or DevOps)
- SQL, Stored Procedures, Functions, and Triggers
- Designing and implementing Data Vault models using metadata driven frameworks
- RDBMS, data modeling, ETL development, and data storage
Responsibilities
- Develop and build sophisticated data analytics and pipelines, ensuring they are robust, scalable, and meet advanced analytical needs.
- Optimize existing data infrastructure and workflows to improve efficiency, performance, and reliability.
- Apply advanced data engineering best practices, including data modeling and ETL processes to deliver high-quality solutions.
- Conduct thorough testing and validation of data pipelines and systems to ensure data accuracy, integrity, and performance standards are met.
- Identify business and data-related issues, using analytical and problem-solving skills to maintain system stability and efficiency.
- Maintain comprehensive documentation of data processes and pipelines.
- Stay current with emerging technologies and trends in data engineering and continuously seek ways to improve processes and technologies used within the team.
Other
- Master's degree in Computer Science, Information Systems, or related field, or foreign degree equivalent, and 2 years of relevant experience as an Engineer, or alternate related acceptable occupation; OR Bachelor's degree in Computer Science, Information Systems, or related field, or foreign degree equivalent, and 5 years of relevant experience as an Engineer or alternate related acceptable occupation.
- 20% of domestic and international travel required
- Provide technical guidance and mentorship to junior data engineers, offering support on complex issues and fostering professional growth within the team.
- Communicate and recommend solutions to stakeholders and communicate with team members regarding project progress and technical issues.
- Contribute to the planning and execution of data engineering projects, providing expertise and ensuring alignment with overall data strategy and project goals.
