Qualifications Bachelor’s degree in Industrial Engineering, Supply Chain, Data Analytics, Information Systems, Computer Science, or a related field 2–3 years of experience in data analysis, business intelligence, process mining, systems analysis, or technical consulting Strong understanding of process flows and material flows Experience working with transactional or operational data Practical experience with SQL and data preparation Strong attention to detail and ability to validate complex data relationships Ability to understand system transactions and connect them to real operational activities Strong troubleshooting and problem-solving skills Good written and verbal communication skills Ability to work effectively with both technical and business stakeholders Technical Skills Strong SQL skills, including joins, aggregations, window functions, and data-quality checks Understanding of data modeling, relational databases, and ETL/ELT concepts Strong Excel skills for data analysis, validation, and reconciliation Experience working with transactional and operational data Ability to understand data structures and connect system transactions to operational and material flows Experience with PQL, particularly when working with Celonis, is preferred Familiarity with process-mining platforms such as Celonis, SAP Signavio Process Intelligence, UiPath Process Mining, IBM Process Mining, or Apromore is preferred; experience with one or more platforms is sufficient Experience with Power BI or Tableau is preferred Familiarity with AI, machine learning, or advanced analytics in process-mining work—such as anomaly detection, root-cause analysis, or predictive insights—is a plus Exposure to APIs, cloud platforms, or data lakes is an asset Core Competencies Understanding of operational and material flows Technical data analysis Data quality and validation Structured troubleshooting Attention to detail Documentation and organization Collaboration and communication Ability to learn new systems and technologies Reliability and ownership Typical Deliverables Data requirements and source-to-target mappings Data dictionaries and process-flow documentation Event logs and process mining data models KPI calculations and technical definitions Dashboards and analytical views Data-quality assessments Test scripts and validation results Technical documentation and configuration records Support materials for workshops and client presentations Why Join Miebach? They will work closely with process mining consultants, data engineers, project managers, and client teams to ensure that the required data, process logic, KPIs, and dashboards are correctly developed and validated.