Senior Data Engineers – IT Data & Analytics

Milwaukee Tool•Brookfield, WI

About The Position

Senior Data Engineers – IT Data & Analytics 13135 West Lisbon Road, Brookfield, WI 53005 Job Duties • 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. • Work to understand detailed analytical requirements and ensure that data solutions effectively support business objectives. • Apply advanced data engineering best practices, including data modeling and ETL processes to deliver high-quality solutions. • Provide technical guidance and mentorship to junior data engineers, offering support on complex issues and fostering professional growth within the team. May lead and mentor team members. • 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. • Communicate and recommend solutions to stakeholders and communicate with team members regarding project progress and technical issues. • Stay current with emerging technologies and trends in data engineering and continuously seek ways to improve processes and technologies used within the team. •Contribute to the planning and execution of data engineering projects, providing expertise and ensuring alignment with overall data strategy and project goals. 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. Work or academic experience must have included: 1. Enterprise data management. 2. Cloud infrastructure and data processing on Microsoft Azure. 3. Designing, building, and optimizing Azure data pipelines. 4. Azure data components (ADLS, ADF, Databricks, Synapse, or DevOps). 5. SQL, Stored Procedures, Functions, and Triggers. 6. Designing and implementing Data Vault models using metadata driven frameworks. 7. RDBMS, data modeling, ETL development, and data storage. 8. Designing and working with distributed and event architectures. 9. Advanced analytics and machine-learning techniques. 10. Data governance and metadata management tools. 20% of domestic and international travel required. #LI-DNI Milwaukee Tool is an equal opportunity employer. Milwaukee Tool, founded in 1924, is a global leader in delivering innovative solutions to the professional construction trades that increase productivity and safety. Milwaukee® is known for their world-leading M12™, M18™, and MX FUEL™ cordless systems, the ground-breaking performance of their cordless innovations, safety solutions, battery-powered outdoor power equipment, jobsite lighting and clean-up, time-saving accessories, and innovative hand tool and PACKOUT™ Modular Storage Products. The company is dedicated to delivering a steady stream of advanced, trade-specific solutions. Milwaukee Tool is a Brookfield, Wisconsin-based subsidiary of Techtronic Industries Co. Ltd. (TTI) (HKEx stock code: 669, ADR symbol: TTNDY). For more information on the full line of Milwaukee® products, please call 1-800-SAWDUST or visit Milwaukee Tool. Join Our Talent Community! Stay connected with us! Even if you’re not ready to apply yet, join our talent community to let us know you are interested in future opportunities.

Requirements

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.
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.
Designing and working with distributed and event architectures.
Advanced analytics and machine-learning techniques.
Data governance and metadata management tools.
20% of domestic and international travel required.

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.
Work to understand detailed analytical requirements and ensure that data solutions effectively support business objectives.
Apply advanced data engineering best practices, including data modeling and ETL processes to deliver high-quality solutions.
Provide technical guidance and mentorship to junior data engineers, offering support on complex issues and fostering professional growth within the team. May lead and mentor team members.
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.
Communicate and recommend solutions to stakeholders and communicate with team members regarding project progress and technical issues.
Stay current with emerging technologies and trends in data engineering and continuously seek ways to improve processes and technologies used within the team.
Contribute to the planning and execution of data engineering projects, providing expertise and ensuring alignment with overall data strategy and project goals.