全职 Data Modeller 工作, 薪水 up to MYR 12,000, Softenger (Malaysia) Federal Territory 公司招聘中 - Ricebowl

Key Responsibilities

Enterprise Data Modelling

• Lead the design and review of enterprise data models across conceptual, logicaland physical layers.
• Establish and maintain enterprise data modelling standards and best practices.
• Develop scalable data structures that support business reporting, analytics and self-service data consumption.
• Ensure consistency and integration across multiple subject areas and business domains.
• Collaborate with business and technical stakeholders to align data structures with business requirements.

Areas of Expertise Required:

Dimensional Modelling

• Star Schema Design
• Snowflake Schema Design
• Fact Table Design
• Dimension Table Design
• Slowly Changing Dimensions (SCD)

Enterprise Modelling

• Conceptual Data Modelling
• Logical Data Modelling
• Physical Data Modelling

Data Warehouse & Analytics Design Review

• Review and assess existing data warehouse and data mart designs.
• Evaluate vendor-delivered data models and recommend improvements.
• Support data warehouse modernisation and transformation initiatives.
• Identify modelling gaps, redundancies and opportunities for optimisation.
• Ensure data models support future analytical and operational requirements.
• Contribute to target-state data architecture and modelling frameworks.

Modern Analytics Platform Enablement

Work closely with architecture, engineering and analytics teams to ensure data models are optimised for modern analytics platforms including:

Data Lakes

• Azure Data Lake Storage (ADLS)
• AWS S3
• Google Cloud Storage

Lakehouse Platforms

• Microsoft Fabric
• Databricks
• Snowflake

Data Warehouse Platforms

• Azure Synapse Analytics
• Snowflake
• BigQuery
• Amazon Redshift

The successful candidate should understand how modelling approaches differ across traditional data warehouses, data lakes and lakehouse environments.

Business Intelligence & Analytics Support

• Design data models that support effective analytics consumption.
• Partner with BI teams to improve semantic layer design.
• Enable self-service analytics capabilities.
• Support enterprise KPI and metric standardization.
• Optimise data structures for reporting performance.

Experience supporting tools such as:

• Power BI
• Tableau
• Qlik
• Looker

Data Governance & Data Quality

• Support enterprise data governance initiatives through effective modelling practices.
• Define and document business definitions, data lineage and metadata requirements.
• Promote data consistency, standardization and reusability.
• Support implementation of data quality and master data management initiatives.
• Collaborate with data owners and stewards to improve data integrity.

Exposure to the following tools is advantageous:

• Microsoft Purview
• Informatica

Performance & Optimisation

• Design models that support efficient query performance and scalability.
• Review and optimise:
• Data storage structures
• Partitioning strategies
• Data refresh performance
• Data loading efficiency
• Semantic model performance
• Identify:
• Data duplication
• Modelling inefficiencies
• Unnecessary transformations
• Technical debt
• Performance bottlenecks

Stakeholder Engagement

• Partner with business users, analytics teams, data engineers and solution architects to understand requirements and translate them into scalable data models.
• Facilitate data modelling workshops and design reviews.
• Present modelling recommendations and design decisions to stakeholders.
• Support delivery of assessment and improvement initiatives.

Typical deliverables include:

• Data Modelling Standards
• Conceptual, Logical and Physical Data Models
• Current-State Data Assessments
• Gap Analysis Reports
• Data Warehouse Design Reviews
• Data Dictionary and Metadata Documentation
• Modelling Recommendations
• Future-State Data Models

Required Qualifications

Experience

• 8+ years of experience in data warehousing, analytics and data modelling.
• Proven experience designing enterprise-scale data models.
• Experience supporting large-scale data warehouse or analytics platforms.
• Experience reviewing and improving existing data warehouse and data mart designs.
• Experience working with cross-functional business and technology teams.

Technical Skills - Must Have

Data Modelling

• Dimensional Modelling
• Star Schema
• Snowflake Schema
• Fact & Dimension Modelling
• Slowly Changing Dimensions
• Conceptual, Logical and Physical Data Modelling

Data Warehousing

• Enterprise Data Warehouse Design
• Data Mart Design
• Data Integration Concepts
• Analytics Data Structures

Cloud Analytics Platforms

• Microsoft Fabric, Databricks, Snowflake or equivalent modern analytics platforms
• Understanding of Data Lake and Lakehouse concepts

Business Intelligence

• Understanding of semantic modelling and analytics consumption patterns
• Experience supporting Power BI, Tableau, Qlik or Looker environments

Data Governance

• Data Lineage
• Metadata Management
• Data Quality Frameworks
• Master Data Management Concepts

Preferred Qualifications

• Experience in Financial Services, Banking, Insurance or other large enterprise environments.
• Experience with Azure Data ecosystem:
• Azure Data Lake
• Azure Synapse Analytics
• Azure Data Factory
• Microsoft Fabric
• Azure SQL
• Databricks
• Microsoft Purview
• Knowledge of modern data architecture and analytics design patterns.
• Experience working with external vendors and system integrators

Pay: RM8,000.00 - RM12,000.00 per month

Benefits:

• Flexible schedule
• Health insurance
• Opportunities for promotion
• Professional development

Work Location: In person