Reporting & dashboards- Build, automate, and maintain executive reports and dashboards end to end using BI tools (e.g., Power BI, Tableau, Looker)- Standardize recurring reports and keep metric definitions consistent so leadership gets timely, trustworthy figures on demand.Centralized data- Consolidate data from across DPU's systems and faculties - marketing, web, admissions, academic, and operations - into one central hub.- Reconcile conflicting figures between sources to establish and maintain a single, trusted source of truth.Data architecture- Design and maintain data models and structure - schemas, relationships, naming, and how data connects across the university.- Partner with IT and system owners to build reliable data pipelines and integrations that feed the central hub.Data quality- Clean, standardize, and validate source data, correcting errors, duplicates, and inconsistencies.- Define and apply quality checks and rules that keep data accurate, complete, and reliable over time.Stakeholders & insight- Work with marketing, web, and other teams to turn business questions into clear, well-defined data outputs.- Translate data into plain-language insight and document sources and reporting logic so outputs are transparent and repeatable.
EducationBachelor's degree in Data Science, Statistics, Computer Science, Information Systems, or a related field.Experience- 3-5 years in a data analyst or similar role.- Strong SQL is a must - querying, transforming, and reconciling data across multiple sources.- Experience consolidating data into a centralized structure (data hub or warehouse)- Solid grasp of data modeling and architecture basics (schemas, relationships , normalization)- Experience building reports and dashboards (e.g., Power BI, Tableau, or Looker)- Strong attention to detail and clear communication with non-technical stakeholders.Skills & Competencies- Programming languages such as Python or R - optional, a plus but not required.- Experience with data in a university or education-sector organization.- Cloud data platforms (e.g., BigQuery, Snowflake, or Azure) and ETL/ELT tools.- Working Thai and English.
