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.

Data analytics and business insights

- Generate actionable insights using advanced analytics and information-visualization techniques to solve business problems.

- Analyze procurement, spend, supplier, invoice, purchase-order and card-related data to identify trends, anomalies and improvement opportunities.

- Validate, interpret and present findings to technical and non-technical stakeholders, including senior leadership.

Analytics engineering and automation

- Develop, maintain and optimize solutions using Python, PySpark, SQL/HQL, BigQuery and Alteryx.

- Automate data preparation, mapping, reconciliation, notifications, monitoring, reporting and repeatable BAU workflows.

- Own scheduled jobs and production use cases, including deployment, validation, troubleshooting, documentation and service continuity.

AI and GenAI enablement

- Identify and deliver practical AI and GenAI use cases for analytics, anomaly detection, knowledge retrieval, summarization and process productivity.

- Apply prompt-engineering fundamentals and responsible AI practices, including human validation, data privacy, security, fairness and transparency.

- Use Python and approved AI tools to prototype, evaluate and operationalize business solutions; define success measures and monitor output quality.

Data platforms, migration and governance

- Support migration of analytical codes, dashboards,



data assets and ingestion processes to cloud platforms such as Lumi/BigQuery.

- Perform feasibility assessments, impact analysis, UAT/DVT, reconciliation, root-cause analysis and business sign-off support.

- Maintain SOPs, process guides, control checks, data lineage, access dependencies and governance documentation.

Reporting, controls and stakeholder management

- Own or support critical reporting and mapping processes, including spend analytics, supplier analytics and compliance monitoring.

- Design and maintain KRIs, governance checks and automated alerts for data or process anomalies.

- Partner with business, product, technology, compliance and operations teams; lead requirement gathering, knowledge transfer and user enablement.

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.

- Transparent documentation, effective stakeholder communication and sustainable knowledge transfer.

📌 GCP Analyst - Finance (Gurugram)
🏢 American Express
📍 Gurugram