Sr Data Modeler (Data Warehousing & Governance) (Klo Job No 133)

Job description

KloudPortal Technology is seeking an experienced Data Modeler to work closely with Data Engineering and Data Governance teams to design, govern, and optimize enterprise data models within a cloud data warehouse ecosystem. This role focuses on translating business requirements into scalable, high-quality data models while ensuring strong metadata management, data quality, and governance standards.

The ideal candidate will have deep expertise in data modeling and data warehousing, with working knowledge of AWS data services. This position emphasizes design, ownership, and governance of data assets, rather than hands-on infrastructure or machine learning development.

Key Responsibilities

• Translate business requirements into long-term conceptual, logical, and physical data models.
• Design and govern data warehouse schemas, including fact and dimension models.
• Analyze and optimize existing data systems for consistency, quality, and performance.
• Collaborate with Data Engineering teams to align data models with ingestion and transformation pipelines.
• Define and maintain enterprise data modeling standards and best practices.
• Review schema changes and system enhancements to ensure cross-platform compatibility.
• Maintain, optimize, and govern metadata and local data models.
• Act as a data asset owner for assigned data domains, ensuring accountability and alignment with enterprise data strategy.
• Work closely with Product Owners, Data Engineers, Data Analysts, Architects, and business stakeholders to deliver data models aligned with the clients data vision.
• Support data quality initiatives by defining validation rules and resolving discrepancies.
• Prepare and maintain data model documentation, SOPs, and governance artifacts.

Technology & Environment

• Cloud Data Warehousing (AWS)
• Amazon Redshift
• AWS Glue Data Catalog
• Amazon S3
• EMR / Spark / Hive (metadata and schema understanding)
• Relational databases (RDS)
• SQL-based analytics platforms

What Were Looking For

• Bachelor’s degree in Computer Science, Statistics, or a related discipline.
• 10+ years of overall IT experience, with strong hands-on experience in data modeling and data warehousing.
• Proven expertise in conceptual, logical, and physical data modeling.
• Strong understanding of data warehouse design principles (fact/dimension modeling, SCDs, schema evolution).
• Working knowledge of AWS data services (Redshift, Glue, S3); deep infrastructure engineering experience is not required.
• Expert knowledge of metadata management and data governance practices.
• Experience acting as a Data Asset Owner or leading data domains.
• Advanced SQL proficiency for data validation, analysis, and reconciliation.
• Strong stakeholder management, leadership, and communication skills.
• Ability to operate effectively in a multi-stakeholder, multi-cultural enterprise environment.
• Data Modeling certifications (ERwin, CDMP, DAMA) are a plus.

Explicit Clarification (to Avoid ML Confusion)

This role does not require machine learning model development. While collaboration with Data Scientists is expected, the focus is on data modeling, data warehousing, metadata management, data quality, and governance.