Data Transformation Analyst

Position: Data Transformation Analyst

Shift Timings : 12 PM to 9 PM (cab facility will be provided)

Job Type : Permanent

Job Summary

The Data Analytics professional is responsible for analyzing procurement and spend data to provide actionable insights that support strategic sourcing, cost optimization, supplier management, and business decision-making. The role focuses on transforming complex data into meaningful dashboards, reports, KPIs, and recommendations for procurement and business stakeholders.

Key Roles & Responsibilities

• Analyze procurement, spend and savings data across suppliers, categories, business units, regions, and time periods to identify trends, opportunities, and potential areas for cost optimization.
• Develop, maintain and enhance Spend and Savings Analytics dashboards and reports using tools such as Power BI, Excel, SQL, and data visualization platforms.
• Consolidate, cleanse, validate, and classify spend data from multiple systems and data sources to improve reporting accuracy and consistency.
• Perform spend classification and category analysis to provide greater visibility into organizational spending patterns.
• Support for the modernization of the reporting landscape, including migration of Power BI products to Databricks Unity Catalog.
• Track and report key procurement metrics and KPIs, including spend by category, supplier concentration, sourcing coverage, savings performance, and procurement compliance.
• Partner with Procurement, Strategic Sourcing, Category Management, Finance, and other business stakeholders to understand analytical and reporting requirements.
• Identify opportunities for supplier consolidation, sourcing initiatives, and cost reduction using data-driven analysis.
• Conduct supplier-level analysis to highlight spend concentration, supplier fragmentation, and opportunities for improved supplier management.
• Create executive-level dashboards and presentations translating analytical findings into clear business insights and recommendations.
• Establish data validation and quality-control processes to ensure the reliability and consistency of procurement reporting.
• Support monthly, quarterly, and annual procurement reporting cycles and ensure timely delivery of dashboards and metrics.
• Automate recurring reports and analytical processes where possible to improve efficiency and reduce manual effort.
• Work with data and technology teams to resolve data-quality, integration, mapping, and reporting issues.
• Maintain reporting documentation, business definitions, KPI logic, and standardized reporting methodologies.
• Support ad-hoc analysis requested by procurement leadership and other stakeholders.

Technical Skills

• Power BI Dashboard development, data visualization, DAX, Power Query
• Microsoft Excel PivotTables, Power Query, advanced formulas and analytical models
• Databricks: Dashboard connections, data preparation for Power BI Dashboards
• SQL Data extraction, transformation, validation and analysis
• Python – Advantageous for data cleansing, automation and advanced analytics
• Strong understanding of data modeling, data quality, spend classification and KPI reporting
• Familiarity with procurement/ERP platforms such as SAP, SAP Ariba or similar systems is advantageous

Core Competencies

• Strong analytical and problem-solving skills
• Procurement and spend-analysis knowledge
• Data visualization and storytelling
• Attention to data accuracy and quality
• Stakeholder management
• Ability to translate business requirements into analytical solutions
• Strong communication and presentation skills
• Ability to manage multiple reporting priorities and deadlines

Typical Qualifications

• Bachelor’s degree in Business, Supply Chain, Data Analytics, Information Systems, or a related discipline.
• Experience in Spend Analytics, Procurement Analytics, Business Intelligence, Reporting, Supply Chain Analytics, or Data Analytics.
• Hands-on experience developing dashboards and analytical reports using Power BI and Excel.
• Experience working with large procurement or financial datasets is preferred.