Senior Data Analyst

2 weeks ago

dindigul, India beBeeSpend Full time

Spend AnalystThis is a highly analytical role that requires the ability to manage, cleanse, classify, and analyze procurement spend data across multiple companies.The ideal candidate will have strong proficiency in Excel and SQL, with the ability to write complex queries and manipulate large datasets.They will also have working knowledge of data cleansing, normalization, and classification concepts, as well as experience with category taxonomies.A bachelor's degree in Engineering, Commerce, Economics, or related fields is required, along with 2–4 years of experience in spend analytics / procurement analytics / data operations.Key Responsibilities:Cleanse and normalize supplier and transaction data using SQL / Excel-based tools.Classify spend into predefined taxonomies (Direct / Indirect; L1/L2/L3 levels).Support mapping and deduplication of supplier records across multiple entities.Validate outputs from AI/ML-driven classification models and correct misclassified data.Generate category roll-ups and dashboards for ongoing reporting cycles.Perform exception handling and QA on recurring spend refresh cycles.Document rules, mapping logic, and change logs for auditability.Support taxonomy refinement and harmonization efforts.Collaborate with engineering and functional teams during data ingestion and refresh cycles.Required Skills & Qualifications:Bachelor's degree in Engineering, Commerce, Economics, or related fields.2–4 years of experience in spend analytics / procurement analytics / data operations.Strong proficiency in Excel and SQL (must be able to write joins, groupings, filters).Working knowledge of data cleansing, normalization, and classification concepts.Familiarity with category taxonomies (e.g., UNSPSC, custom corporate taxonomy).Experience with Power BI, Tableau, or similar BI tools preferred.Understanding of procurement or finance data (POs, invoices, supplier master, GL).Detail-oriented mindset with ability to work through large datasets systematically.Behavioral Competencies:Structured and methodical problem-solver.Comfortable working in high-volume, iterative data environments.Curious, proactive learner with a 'get it right' attitude.Strong written and verbal communication skills for documentation and QA reporting.Ability to work across time zones with US-based client teams.

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