Data Engineer (Celonis)

Job Title : Data Engineer (Celonis)

Location : Remote- US/ Canada

Key Responsibilities

• Connect, extract, transform, and load data from diverse cloud and on‐premise systems (Azure, Oracle, SAP, BMC, ServiceNow, Salesforce, etc.) into process mining tools.
• Validate data accuracy between source systems and process mining platforms.
• Create KPIs and actionable insights to identify inefficiencies and root causes in business processes.
• Work with ERP and enterprise systems to understand data structures, reports, and formats.
• Develop workflows to monitor processes, detect anomalies, and implement automated corrective actions (Action‐engine, Action‐flows).
• Map processes, identify non‐value‐add steps, and recommend lean/agile improvements.
• Collaborate with technical and non‐technical stakeholders to design and prioritize process mining initiatives.
• Visualize and build dashboards aligned with client expectations.
• Apply critical thinking and problem‐solving to business challenges using process mining best practices.

Required Technical Skills

• 1–2 years of experience in Celonis Process Mining as a Data Engineer/Data Scientist.
• Hands‐on experience with ETL/ELT and BI tools (Tableau, Power BI).
• Strong SQL/PQL scripting skills; ability to write complex queries (joins, unions, window functions).
• Knowledge of process improvement techniques, analytics, and process mining methodologies.
• Basic Python scripting (Numpy, Pandas, Seaborn, Matplotlib, Scikit‐Learn).

Desired Technical Skills

• Experience with other process/task mining tools (Signavio, Software AG, FIQ, Soroco).
• Familiarity with ERP/CRM systems (SAP, Oracle, MS Dynamics, ServiceNow, Salesforce, Remedy).
• Exposure to ML modeling using Python or R.

Professional Skills

• Strong communication and presentation abilities.
• Solid understanding of business processes across domains (Finance, Procurement, Banking, Insurance, HR).

Soft Skills

• Self‐starter with quick learning ability.
• Adaptable to new technologies and process improvement techniques.
• Flexibility to work across time zones for global rollouts.

Education

• Bachelor's degree in Computer Science, Information Technology, or equivalent.
• Data Science diploma/certification preferred.