Business Intelligence Technician

Preferred: Minimum 1 year in developing and designing data management solutions or 1 year of practical data science experience using MS Excel, Power BI, PowerQuery with a proven track record of solving critical business problems and uncovering new business opportunities. Experience working in projects or small teams in Production environment. Technical knowledge 1\. Experience designing and training models, integrating data from different systems, and cleaning data. 2\. Experience of Windows and O365 platform. 3\. Solid experience of data visualization tools such as Power BI and/or Pyqtgraph, Tableau, etc. 4\. Ability to write complex queries that are accessible, secure, and perform in an optimized manner with an ability to output to different types of consumers and systems. 5\. Basic understanding of SQL to perform data collection of large datasets. 6\. Basic understanding of relational and non-relational database systems. 7\. Basic understanding of cloud development platforms such as Power Apps, Azure and their associated data storage options. 8\. Experience using MAPICS. #LI-ME1

Years and area of experience required: 2 years of technical or administrative support in related areas. Preferred: Minimum 1 year in developing and designing data management solutions or 1 year of practical data science experience using MS Excel, Power BI, PowerQuery with a proven track record of solving critical business problems and uncovering new business opportunities. Experience working in projects or small teams in Production environment. Technical knowledge 1\. Experience designing and training models, integrating data from different systems, and cleaning data. 2\. Experience of Windows and O365 platform. 3\. Solid experience of data visualization tools such as Power BI and/or Pyqtgraph, Tableau, etc. 4\. Ability to write complex queries that are accessible, secure, and perform in an optimized manner with an ability to output to different types of consumers and systems. 5\. Basic understanding of SQL to perform data collection of large datasets. 6\. Basic understanding of relational and non-relational database systems. 7\. Basic understanding of cloud development platforms such as Power Apps, Azure and their associated data storage options. 8\. Experience using MAPICS.

Support the Business Intelligence, Data Management and Analytics Team with the execution of its roadmap enabling stategic use of data at Eaton. Combine technical skills, a passion for creative problem solving to build great data management solutions that will enable better, quicker and real time decision making. Lead BPI events to data collection, data management and data presentation processes. Participate in RIEs to assist with MAPICS direct data collection and requirements analysis processes. Provide support on MAPICS system knowledge and processes. Job Responsibilities 1\. Streamline processes and create efficiencies in the way the various departments and team members use applications, technology, and practices to collect, analyze, and present data across business functions. Proactively seek opportunities to improve data quality. 2\. Provide maintenance and technical support to homegrown systems in O365 (e.g. material request system, replenishment system, etc). 3\. Provide maintenance and technical support to the reports are running on Power BI Service such as: Programa Kaizen y Sugerencia, Action Tracker, Allocation Tracker Report, ECO’s Report, Project Portfolio Report, Haina Load Performance Report. 4\. Provide system knowledge support to MAPICS user in business processes, such as: creation of MOs under deviation, creation of queries and reports to extract data from MAPICS, receipt of breakers by warranty, PMC, etc. 5\. Provide maintenance and technical support to reports from MAPICS AA environment used by finance team. 6\. Derive, interpret and effectively deliver the results of data analysis using visualization techniques, tools, custom applications, or by narrating stories about the solutions to business problems. 7\. Understand traditional and new data analysis methods that can build statistical models and discover patterns in data. 8\. Work directly with business stakeholders and engineering teams, ask the right questions to create high quality solutions that solve end-user problems. 9\. Utilize a broad range of techniques in machine learning, data mining, statistics, and big data interrogation methods. 10\. Provide work estimates and participate in design and implementation reviews. 11\. Execute agile work plans for iterative and incremental project delivery. ## Qualifications: