Job Description

SmartOSC is seeking an Analytics Engineer (Data Domain Architect) to join our Enterprise Data & AI project team serving an international enterprise client. You will turn business requirements into trusted, reusable data products, owning domain data models, semantic layers, metadata and data quality to power analytics, self-service BI and AI use cases.

Key Deliverables & Responsibilities

– Design and maintain conceptual, logical, dimensional and semantic data models for assigned business domains, aligned with enterprise architecture standards.

– Translate business requirements from Data Product Managers into data structures, entity relationships, hierarchies and business rules.

– Build semantic models, metric layers and reusable KPI frameworks to keep business definitions consistent across reports, dashboards and AI solutions.

– Design analytics-ready, certified data products and reusable transformations in collaboration with Data Engineers.

– Maintain business and technical metadata, lineage, data dictionaries and documentation so data products are cataloged and discoverable.

– Define data quality rules and controls; support root cause analysis and remediation together with Data Governance teams.

– Design AI/ML-ready datasets and partner with AI Engineers and Data Scientists to ensure feature consistency and data reuse.

– Support impact assessment and change management for data model changes.

Requirements

– Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, Statistics or a related field.

– 3+ years of experience in Analytics Engineering, Business Intelligence, Data Architecture or Data Warehousing.

– Strong data modeling skills (conceptual, logical, dimensional, semantic) and hands-on experience building semantic layers and analytics-ready datasets.

– Strong SQL for data validation, profiling and analytical problem-solving.

– Solid knowledge of data governance, metadata management, data lineage and data quality practices.

– Ability to translate business needs into data solutions and explain complex data concepts to technical and non-technical stakeholders.

– Good command of English (required).

Nice to Have

– Experience with Microsoft Fabric, Power BI, Azure, Databricks, Snowflake or similar cloud data platforms.

– Python for data analysis, transformation, automation and AI/ML enablement.

– Experience supporting AI, machine learning or advanced analytics initiatives.

– Certifications in data, cloud or enterprise architecture (e.g., Microsoft, AWS, Azure, GCP, DAMA, TOGAF).

– Domain experience in aviation/travel, commercial, customer, loyalty, finance or operations.

Benefits

At SmartOSC, we offer the best to your values:

– Attractive salary package

– Salary review twice a year

– Flexible working hours (between 7:30am – 7:30pm on staff’s preference)

– Premium health care 

– Working in one of the largest digital transformation agencies in Asia – Professional English environment

– Firm’s Certified Qualifications Sponsorship for career development

– Annual company trip inside or outside Vietnam

– Other fun activities: happy hour, quarterly team building, football club, yoga club, swimming club, charity activities, etc.

– Free entertainment parties: Birthday party, Anniversary party, Sum-up Party, Year-End Party, etc

Personal Data Consent Notice

By submitting your resume for this position, you acknowledge and consent that the Company may collect, use, store, disclose (where necessary), and otherwise process your personal data for recruitment-related purposes, including evaluating your application, communicating with you, and making hiring decisions. Your personal data may be shared with relevant third parties involved in the recruitment process on a need-to-know basis. You acknowledge and consent that the Company shall retain your personal data for as long as necessary to fulfil the above purposes or to comply with applicable legal obligations. Where permitted by applicable law, you may submit a written request for the deletion of your personal data.