About this role
Drive business value through procurement and spend analytics, cloud-based data solutions, reporting automation, AI-enabled insights, and strong data governance. The role combines hands-on technical delivery with business analysis, stakeholder engagement, migration support, validation, and production ownership.
Required skills and qualifications
- Bachelor’s degree in engineering, computer science, statistics, mathematics, business analytics or a related field.
- 4–5 years of relevant experience in data analytics, business intelligence, reporting automation or analytics consulting.
- Strong procurement process and business knowledge; experience with P2P or spend analytics is preferred.
- Strong hands-on knowledge of Python, Pandas, PySpark, SQL/HQL and cloud data warehouses such as BigQuery.
- Strong Alteryx capability covering workflow development, data blending, transformation, validation, optimization and scheduling.
- Working knowledge of AI/ML and GenAI concepts, prompt design, AI-assisted analytics, model/output evaluation and responsible AI controls.
- Experience with Tableau capabilities, including dashboard development and interactive analytics; Power BI knowledge is an advantage.
- Advanced Excel and PowerPoint skills, with strong analytical, troubleshooting and presentation capability.
- Experience managing enterprise-level initiatives and enhancing or automating reporting structures.
- Ability to work autonomously, make sound decisions under ambiguity and time pressure, and collaborate effectively across teams.
- Excellent written and verbal communication skills, with the ability to explain technical findings to non-technical audiences.
- Curiosity and willingness to learn new open-source technologies, languages and AI-enabled methods.
Preferred experience
- Cloud analytics platforms, code repositories, deployment pipelines and scheduled workflow management.
- Data migration, cutover, UAT/DVT, reconciliation and production stabilization.
- Data privacy, PII handling, access governance, controls and compliance reporting.
- Process documentation, SOP creation, transition planning and hands-on knowledge transfer.
Success measures
- Reliable continuity of critical reporting, mapping and monitoring processes.
- Measurable reduction in manual effort through Python, Alteryx and AI-enabled automation.
- Accurate, well-governed and timely analytical outputs with clear validation evidence.
- Successful migration and stabilization of data assets, codes and dashboards.
- Clear documentation, effective stakeholder communication and sustainable knowledge transfer.