Job Title: Data Engineer (Celonis)
Location: Remote- US/ Canada
Term: Long Term Contract
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.