Data Model Engineer

Описание

Join our team in building a modern, high-impact Analytical Platform for one of the largest integrated resort and entertainment companies in Southeast Asia. This platform will serve as a unified environment for data collection, transformation, analytics, and AI-driven insights—powering decisions across marketing, operations, gaming, and more.

You’ll work closely with Data Architects, Data Engineer, Business Analyst and DevOps Engineers to design and implement scalable data solutions.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, or a related field.
• 3+ years of experience in data modeling, data architecture, or data engineering roles.
• Proficiency with data modeling tools (e.g., ER/Studio, ERwin, dbt, SQL Developer Data Modeler).
• Strong SQL skills and experience with relational and dimensional database modeling (e.g., star and snowflake schemas).
• Experience with modern data warehouses (e.g., Snowflake, Redshift, Yellowbrick) and ETL/ELT tools.
• Understanding of data governance, metadata management, and data cataloging tools.
• Experience collaborating in Agile/Scrum teams and working with version-controlled data models (e.g., via Git).

Nice to have skills

• Experience working with data lakehouse architectures or modeling for big data environments (e.g., Delta Lake, Apache Iceberg).
• Familiarity with business intelligence tools (e.g., Tableau, Power BI, Looker).
• Knowledge of data quality frameworks and observability best practices.
• Experience working in regulated industries (e.g., gaming, finance, hospitality).

Responsibilities:

• Design and implement conceptual, logical, and physical data models that support enterprise reporting, analytics, and operational processes.
• Develop and maintain data dictionaries, entity-relationship (ER) diagrams, and metadata management solutions.
• Collaborate with data engineers to optimize data structures and ensure proper integration with data pipelines.
• Translate complex business requirements into scalable and efficient data models.
• Enforce data modeling best practices, including normalization, denormalization, indexing, and partitioning strategies.
• Ensure data models are aligned with master data and data governance standards.
• Conduct model reviews and provide documentation and training to technical and non-technical stakeholders.
• Participate in performance tuning and troubleshooting of large-scale data models and queries.

Benefits

• 35 absence days per year for work-life balance
• Udemy courses of your choice
• English courses with native-speaker
• Regular soft-skills trainings
• Excellence Сenters meetups
• Online/offline team-buildings
• Business trips