Master Data Coordinator III

Position Summary:

As data becomes increasingly critical to operational efficiency, business intelligence, and digital transformation, the Data Engineer plays an important role in supporting initiatives that enhance the quality, governance, integration, and accessibility of enterprise data across the organization. This role supports the Data Services team by developing and maintaining data pipelines, supporting Master Data Management (MDM) and Data Quality (DQ) processes, and enabling trusted data delivery for reporting, analytics, and business operations.

Working closely with data engineers, architects, business stakeholders, and analytics teams, the Data Engineer helps ensure that customer, supplier, item, and other critical master data assets are accurate, consistent, and available across enterprise platforms. This position provides an excellent opportunity for recent graduates to gain hands-on experience with modern data technologies, cloud platforms, data governance practices, and enterprise data management solutions while contributing to initiatives that improve data-driven decision-making throughout the organization.

Key Responsibilities

Data Engineering & Integration

• Assist in developing, testing, and maintaining data pipelines and ETL processes.
• Support data integration activities from multiple enterprise systems and data sources.
• Help monitor and troubleshoot data processing jobs to ensure reliability and performance.
• Participate in data migration, validation, and reconciliation activities.

Master Data Management (MDM)

• Support the maintenance and enhancement of enterprise master data models.
• Assist in data quality analysis, data cleansing, and governance activities.
• Help document business rules, data definitions, and master data standards.
• Participate in data stewardship initiatives to improve data consistency and accuracy across systems.

Data Modeling & Analytics

• Assist in creating conceptual, logical, and physical data models under the guidance of senior team members.
• Support data warehousing and business intelligence initiatives.
• Collaborate with stakeholders to understand reporting and analytics requirements.
• Help create documentation, process diagrams, and data flow mappings.

Cloud & Modern Data Platforms

• Support development activities within Databricks and cloud-based data environments.
• Learn and apply technologies such as Apache Spark, Delta Lake, SQL, and Python.
• Participate in CI/CD, DevOps, and automation initiatives related to data engineering solutions.

Collaboration & Continuous Improvement

• Work closely with MDM, Data Quality, Integration, and Analytics teams.
• Participate in Agile ceremonies, sprint planning, and team discussions.
• Contribute ideas to improve data processes, automation, and operational efficiency.
• Stay current with emerging data engineering and analytics technologies.

Qualifications

Required Education

• Bachelor's Degree in Computer Science, Data Science, Information Technology, Computer Engineering, Industrial Engineering, Mathematics, Statistics, or a related technical discipline.

Experience

• Fresh graduates are encouraged to apply.
• Internship, academic projects, or capstone experience involving databases, ETL, analytics, or cloud technologies is an advantage.

Preferred Technical Skills

Database & Query Languages

• Basic knowledge of SQL
• Understanding of relational databases and data structures
• Programming
• Exposure to Python, Java, Scala, or similar programming languages
• Data & Analytics
• Basic understanding of:
• Data Warehousing
• Data Quality concepts
• Data Governance
• Master Data Management (MDM)
• Business Intelligence reporting
• Mathematics
• Statistics
• Or a related technical discipline
• Cloud & Modern Data Platforms (Exposure to one or more of the following preferred):
• Databricks
• Azure
• AWS
• Google Cloud Platform (GCP)
• Apache Spark

Additional Preferred Skills

• Familiarity with Git or version control systems
• Knowledge of Agile methodologies
• Experience with Tableau, Power BI, or similar reporting tools
• Understanding of ETL concepts and data integration processes