Our client is seeking an experienced Data & Analytics Engineer to help drive data initiatives by building scalable backend data infrastructure that powers reporting and process insights. This role is split evenly between process mining work using Celonis and broader data engineering efforts. You’ll be involved in both developing new pipelines and optimizing existing ones to ensure reliable, high-performance data delivery across the organization.
Key Responsibilities:
- Design and implement backend data pipelines to support business intelligence and process analysis platforms (e.g., Celonis, Power BI).
- Write and optimize SQL queries and procedures for ETL processes.
- Use Python to build automation tools and data transformation scripts.
- Maintain and improve data integration workflows, ensuring accuracy and performance.
- Develop and manage structured datasets and data models aligned with stakeholder requirements.
- Troubleshoot and resolve data issues, ensuring data quality and pipeline stability.
- Collaborate closely with analytics, engineering, and business teams to align solutions with organizational goals.
- Maintain clear documentation for workflows, models, and data architecture.
- Stay up to date on evolving data engineering practices and tools in the analytics and process mining space.
Role Focus:
- Work Distribution: 50% Celonis (process mining), 50% general analytics/data engineering.
- Pipeline Work: Balanced focus between building new data pipelines and maintaining or optimizing existing ones.
What You Bring:
- Strong SQL development and performance tuning skills.
- Proficiency in Python for data manipulation and automation.
- Hands-on experience with process mining tools (Celonis preferred).
- Solid understanding of data modeling and ETL principles.
- Strong collaboration and communication skills.
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