Celonis Data Engineer/Consultant Infosys

  • company name Infosys
  • working location Office Location
  • job type Full Time

Experience: 2 - 2 years required

Pay:

Salary Information not included

Type: Full Time

Location: All India

Skills: SQL, Python, Analytical skills, data modelling, ERP systems like SAP, Business Concepts

About Infosys

Job Description

You should have at least 2+ years of relevant work experience in process and data modelling. Experience in working with data from ERP systems like SAP is required. A proven track record in using SQL and Python is necessary for this role. Strong analytical skills and an affinity with business concepts are crucial. Possessing a Celonis Data Engineer/Implementation Professional certification will be considered an advantage. Previous Celonis project experience will be a big plus. As a part of the team driving Celonis initiatives, you will be involved in diving into business processes to identify root causes, quantify potential, and implement improvement initiatives to enhance business efficiency. Your responsibilities will include setting up and maintaining data models that will form the basis of analyses. Collaboration with business analysts to develop customized analytics for business performance measurement and data-driven decision-making is essential. You will also be accountable for establishing a data dictionary and maintaining data governance on the created structure. Identifying the best strategy for data collection, ensuring data quality, and collaborating with stakeholders responsible for data input to accurately measure and track necessary information are part of your role. Working closely with source system experts to ensure correct setup for gathering relevant information and supporting effective data structures is crucial. Furthermore, you will be responsible for creating and maintaining comprehensive documentation for data models, processes, and systems to facilitate knowledge sharing within the team. Strong communication skills are required to convey data structural concepts and ideas to both technical and non-technical stakeholders effectively.,