Sr Specialist - Process Mining & Automation

Job Description

Role involves designing, developing, and maintaining data pipelines to support analytics and reporting requirements. Responsibilities include collaborating with cross-functional teams to gather data requirements, optimize data models, and ensure data quality. The ideal candidate should have strong Database SQL and PQL skills, experience with cloud-based data technologies, and a background in data engineering or a related field Job Description Major accountabilities: Designing and implementing data pipelines to extract, transform, and load data from various sources into Celonis for analysis. Collaborating with business teams, business analysts, and other stakeholders to understand their data requirements and ensure data is delivered accurately and efficiently. Monitoring and maintaining data quality, performance, and integrity within the Celonis platform to support effective decision-making and business processes Contribute enterprise grade and state of the art Solution Design and Architecture with maximizing re-usability, configurability and scalability. Ensure top class and state of the art engineering delivery, code management, automation and strive for highest efficiency. Ensure the overall user experience is taken into account when designing deploying new solutions and services. Ensure adherence to Security and Compliance policies and procedures as well as with other Novartis guidelines and standards. Deliver as per agreed timelines and budget. Effectively engage with the chosen SI Partner(s) and collaboratively strive to deliver business value Minimum Requirements: At least 7+ years of experience in Data bases, data integration and data modeling. Min 2 yrs of experience in Celonis process mining Ability to lead teams and drive completion of projects as per business requirements Working in multi-national context and across countries. Experience in managing celonis platform, optimization of APC consumption Celonis process mining, Data bases, PQL, SQL, Data Modeling, Data Integration Business Partnering, Change Management, IT Service Delivery and Performance Management.