- The Data Analytics Engineer will be responsible for designing, developing, and optimizing analytical solutions that support enterprise-wide decision-making, governance, and process efficiency.

- This role requires a strong background in process mining, SQL development, data integration, and ETL pipeline engineering.

- The candidate will partner closely with business stakeholders, process owners, product teams, and technical experts to analyze end-to-end business processes, identify inefficiencies, and translate operational data into actionable insights.

- A key focus of this role is building robust and scalable data models, integrating data from SAP, Ariba, EMS tools, Microsoft 365, and other enterprise platforms to support advanced analytics, reporting, and AI-driven automation use cases.

- The Data Analytics Engineer will be expected to evaluate and implement process mining methodologies, derive process metrics, and collaborate on continuous improvement initiatives.

- In addition, the candidate will support the development of ML- and GenAI-driven solutions, making the role more innovation-focused than traditional analytics alone.

- They will contribute to designing automated workflows, building predictive models, integrating AI services with enterprise systems, and enabling self-service analytics capabilities.

- The role demands a strong command of SQL Server, hands-on exposure to ETL tools, and depth in data modeling, along with the ability to understand complex functional workflows across procurement, finance, supply chain, and operational domains.

- The ideal candidate is detail-oriented, analytical, and capable of breaking down complex business requirements into well-structured technical solutions.

- They should have experience working with enterprise applications such as SAP and Ariba, familiarity with EMS tools, and practical exposure to Microsoft 365 integrations.

- The role requires strong problem-solving skills, collaboration with cross-functional teams, clear communication, and the ability to work in a fast-paced environment while ensuring high data accuracy, reliability, and governance.

- Candidates with hands-on experience in ML/GenAI solution development, process mining platforms (e.g., Celonis, UiPath Process Mining, Power BI Process Mining), and enterprise data engineering will be preferred