Data Enrichment Specialist

Back Job Details Data Enrichment Specialist Apply for this job Location Chennai / Remote Experience 3-6 Years Employment Type Full-Time Experience: 3-6 Years Employment Type: Full-Time Role Summary DataXWorks is hiring a Data Enrichment Specialist to support enterprise data enrichment, metadata improvement, taxonomy alignment, and structured dataset preparation. The role involves improving raw data by adding missing attributes, validating information, standardizing records, and making datasets more useful for analytics, AI, marketing, and business operations. Key Responsibilities Enrich business, product, customer, catalog, document, or domain-specific datasets. Add, validate, and standardize metadata, tags, attributes, categories, and classifications. Identify missing, duplicate, incomplete, or inconsistent records. Support entity resolution, taxonomy alignment, and data normalization workflows. Validate enriched data against source references and project guidelines. Work with data operations and QA teams to improve dataset quality. Maintain documentation of enrichment rules, assumptions, and quality issues. Required Skills & Experience 2+ years of experience in data enrichment, data research, data cleansing, catalog operations, or data operations. Strong attention to detail and research ability. Ability to work with structured datasets, spreadsheets, and classification rules. Familiarity with metadata, taxonomy, entity resolution, or data standardization is preferred. Good communication and documentation skills. Experience in retail, eCommerce, B2B data, BFSI, or healthcare datasets is a plus. Why Join DataXWorks You will help enterprises turn raw, incomplete, and fragmented data into structured, usable, AI-ready datasets. Apply for this job Back Job Details Data Enrichment Specialist Apply for this job Location Chennai / Remote Experience 3-6 Years Employment Type Full-Time Experience: 3-6 Years Employment Type: Full-Time Role Summary DataXWorks is hiring a Data Enrichment Specialist to support enterprise data enrichment, metadata improvement, taxonomy alignment, and structured dataset preparation. The role involves improving raw data by adding missing attributes, validating information, standardizing records, and making datasets more useful for analytics, AI, marketing, and business operations. Key Responsibilities Enrich business, product, customer, catalog, document, or domain-specific datasets. Add, validate, and standardize metadata, tags, attributes, categories, and classifications. Identify missing, duplicate, incomplete, or inconsistent records. Support entity resolution, taxonomy alignment, and data normalization workflows. Validate enriched data against source references and project guidelines. Work with data operations and QA teams to improve dataset quality. Maintain documentation of enrichment rules, assumptions, and quality issues. Required Skills & Experience 2+ years of experience in data enrichment, data research, data cleansing, catalog operations, or data operations. Strong attention to detail and research ability. Ability to work with structured datasets, spreadsheets, and classification rules. Familiarity with metadata, taxonomy, entity resolution, or data standardization is preferred. Good communication and documentation skills. Experience in retail, eCommerce, B2B data, BFSI, or healthcare datasets is a plus. Why Join DataXWorks You will help enterprises turn raw, incomplete, and fragmented data into structured, usable, AI-ready datasets. Apply for this job Experience: 3-6 Years Employment Type: Full-Time Role Summary DataXWorks is hiring a Data Enrichment Specialist to support enterprise data enrichment, metadata improvement, taxonomy alignment, and structured dataset preparation. The role involves improving raw data by adding missing attributes, validating information, standardizing records, and making datasets more useful for analytics, AI, marketing, and business operations. Key Responsibilities Enrich business, product, customer, catalog, document, or domain-specific datasets. Add, validate, and standardize metadata, tags, attributes, categories, and classifications. Identify missing, duplicate, incomp .