Data Engineer

Role - Data Engineer Experience - 5 – 12 Years Role Overview We are looking for a highly skilled Data Engineer with strong exposure to Procurement domain and Master Data Management (MDM). The ideal candidate will work at the intersection of data engineering, procurement analytics, and data governance, building scalable data pipelines and ensuring high-quality master data across systems. This role requires expertise in open-source technologies, data architecture, and procurement data models (supplier, vendor, material master).

Roles and Responsibilities Data Engineering & Architecture Design, build, and maintain scalable data pipelines and data platforms for procurement and supply chain data Develop and optimize ETL/ELT pipelines for ingesting large, complex datasets Build and manage data lakes / warehouses using modern open-source stacks Ensure high performance, reliability, and scalability of data systems Master Data Management (MDM) Develop and maintain Master Data Management frameworks for supplier, vendor, and material master data Ensure data quality, consistency, governance, and standardization across systems Implement data validation, cleansing, and enrichment processes Define and enforce data governance policies, taxonomies, and naming conventions Procurement Data & Domain Integration Work closely with Procurement, Finance, and Supply Chain teams to understand data requirements Manage supplier master data, spend data, contract data, and catalog data Enable data-driven procurement insights (spend analytics, vendor performance, risk analysis) Integrate data from ERP systems (SAP/Ariba/Coupa) and external sources Data Governance & Quality Establish and monitor data quality KPIs and SLAs Identify and resolve data inconsistencies, duplication, and integrity issues Support data audits, compliance, and regulatory requirements Collaboration & Stakeholder Management Collaborate with data scientists, analysts, and product teams to deliver business insights Partner with engineering teams to build self-service data platforms Communicate complex data concepts to business stakeholders Technical Skills (Must-Have) Core Data Engineering Strong experience with Python, SQL Experience with ETL tools / frameworks (Airflow, dbt, etc.) Hands-on with data warehousing (Snowflake, BigQuery, Redshift) Open Source Technologies (Important) Apache Spark / Hadoop ecosystem Kafka / streaming frameworks Airflow / Prefect Delta Lake / Iceberg MDM & Data Governance Experience with Master Data Management tools or frameworks Strong understanding of data modeling, data lineage, and metadata management Knowledge of data quality frameworks and governance practices Procurement Systems (Preferred) Exposure to SAP (MM), Ariba, Coupa, Ivalua, GEP, Zycus Understanding of procurement lifecycle and supplier data models Required Skills Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field 4–10 years of relevant experience in Data Engineering, with hands-on exposure to Master Data Management (MDM) and/or Procurement/Supply Chain data Proven experience in building and managing scalable data pipelines, data lakes, and data warehouses using modern architectures Strong understanding of data modeling (dimensional & relational), data governance, and data quality frameworks Hands-on experience with open-source data technologies such as Apache Spark, Airflow, Kafka, dbt, etc. Exposure to ERP and procurement platforms (SAP MM, Ariba, Coupa, Ivalua, GEP, Zycus) and understanding of supplier/vendor master data structures Experience working on MDM implementations, data standardization, deduplication, and governance frameworks Strong proficiency in SQL and Python, with experience in handling large-scale datasets Familiarity with cloud platforms (AWS, Azure, or GCP) and modern data stack Experience working in cross-functional and global stakeholder environments Strong problem-solving skills with the ability to translate business requirements into scalable data solutions