Associate Data Governance and Modeller

Data Engineering and Data Governance teams

This role will involve building conceptual and physical data models, designing data flows, implementing data strategies, and maintaining metadata frameworks that support enterprise-wide analytics and decision-making. You will collaborate closely with Product Owners, Data Scientists, Data Engineers, Analysts, Architects, and Software Developers to ensure alignment with overall data architecture goals.

Key Responsibilities

• Translate business requirements into scalable long-term solution data models.
  
• Analyze, evaluate, and optimize existing data systems for accuracy and efficiency.
  
• Collaborate with development teams to design conceptual data models, logical architectures, and data flows.
  
• Establish and maintain best practices for data coding and data modeling standards.
  
• Review system enhancements for cross-platform compatibility and architectural alignment.
  
• Implement data strategies and develop physical data models supporting enterprise initiatives.
  
• Maintain, update, and optimize metadata and local data models.
  
• Identify variances, discrepancies, and performance gaps in implemented data systems.
  
• Troubleshoot and enhance data models and pipelines for optimal performance.
  
• Work collaboratively with Product Owners, Data Scientists, Data Engineers, Data Analysts, Architects, and other stakeholders to deliver models aligned with the client's data vision.
  
• Prepare model documentation, SOPs, and training materials to support data governance and continuous improvement.
  

Technology Stack

AWS S3, EMR, Redshift, Lambda, Glue, RDS, and SQL-based data systems.

What Were Looking For

• Bachelor's degree in Computer Science, Statistics, or a related field.
  
• 10+ years of overall IT experience, including 5-8 years of hands-on data modelling or machine learning experience in production environments with a proven track record of deliveries.
  
• Expert-level knowledge of

  metadata management

  and related tooling.
• Strong SQL proficiency and hands-on experience across AWS data services (S3, EMR, Redshift, Lambda, Glue, RDS).
  
• Solid understanding of mathematical concepts, statistical analysis, and data foundations.
  
• Advanced troubleshooting skills with the ability to resolve complex data issues.
  
• Excellent communication, presentation, and stakeholder management skills.
  
• Ability to collaborate effectively in multi-cultural and cross-functional environments.
  
• Data Modeling certifications (e.g., ERwin, DAMA, CDMP) are a strong plus.