DDM, BI Developer

Business Intelligence (BI) Developer Department: Data, Development AI Level: DDM Location: Bangkok, Thailand Purpose of the Role We are seeking a highly experienced Business Intelligence Developer to elevate our data capabilities and drive enterprise-wide analytics excellence. This role is central to building scalable data models, orchestrating modern BI solutions on Google Cloud Platform (GCP), and delivering impactful insights via Power BI and other cutting-edge tools. You’ll work at the crossroads of data engineering, analysis, and strategy—enabling actionable decision-making across all business units through robust data pipelines, data marts, semantic models, and automated dashboards. A strong foundation in BigQuery, Power BI, and data governance is essential. Key Responsibilities 1. Requirements Gathering Stakeholder Engagement 1.1 Partner with business users to understand their data and reporting requirements. 1.2 Translate business needs into technical specifications for BI solutions. 1.3 Facilitate workshops and discovery sessions with cross-functional stakeholders. 2. Data Architecture Modeling 2.1 Design and maintain scalable data marts, star/snowflake schemas, and semantic models in BigQuery. 2.2 Collaborate with data engineers to define and optimize ETL/ELT pipelines using GCP tools (e.g., Dataflow, Cloud Composer, Cloud Functions). 2.3 Develop logical and physical data models that support self-service analytics and performance. 3. BI Development Visualization Build visually engaging, interactive dashboards in Power BI, ensuring scalability, usability, and performance. 3.1 Implement row-level security, DAX measures, and Power BI Dataflows for scalable asset reuse. 3.2 Leverage Looker or Looker Studio as needed to complement visual storytelling across platforms. 4. Data Quality Cataloging 4.1 Integrate with Google Cloud Data Catalog to maintain standardized data definitions, business glossaries, and data lineage. 4.2 Work closely with data stewards and governance teams to enforce data quality, consistency, and compliance. 5. Advanced Analytics Enablement 5.1 Partner with data scientists to productionize ML features and predictive models into BI dashboards. 5.2 Support forecasting, segmentation, and trend analysis using statistical or machine learning techniques when appropriate. 6. Automation Optimization 6.1 Automate recurring reporting using tools like Power BI Service, BigQuery Scheduled Queries, and Cloud Composer workflows. 6.2 Monitor and optimize BI solutions for performance, cost efficiency, and reliability on GCP. 7. Governance, Security Compliance 7.1 Enforce best practices for report version control, dataset governance, and Power BI Premium workspace management. 7.2 Ensure adherence to data privacy laws (e.g., PDPA, GDPR) and internal compliance standards. 8. Documentation Training 8.1 Maintain up-to-date documentation for dashboards, datasets, and models using tools like Confluence or Git. 8.2 Conduct knowledge-sharing sessions and training to promote self-service analytics culture. Qualifications Required - Bachelor’s degree in Computer Science, Data Science, Engineering, or related discipline. - 10+ years of experience in Business Intelligence, Data Engineering, or Analytics. - Deep expertise in Power BI, including DAX, Power Query (M), RLS, and Premium workspace administration. - Advanced proficiency in Google BigQuery, including SQL optimization, partitioning, clustering, and performance tuning. - Strong understanding of data warehousing concepts, dimensional modeling, and data pipelines. - Experience with data governance, data cataloging, and business glossaries. - Experience in GCP BI tools (Looker, Looker Studio) is a plus. Preferred - Proficiency in Python, SQL, and scripting for automation and data wrangling. - Experience with dbt (data build tool) and version-controlled development. - Familiarity with Git, JIRA, Agile methodologies, and CI/CD in a data context. - Certifications such as: - Google Professional Data Engineer - Microsoft Certified: Power BI Data Analyst Associate - Looker LookML Developer Certification KPIs Quantitative Uptime and performance of BI dashboards. Number of automated reports vs. manual. Power BI workspace usage, adoption, and engagement metrics. Reduction in ad hoc reporting through self-service enablement. Qualitative Stakeholder satisfaction and feedback. Clarity and impact of data storytelling. Accuracy and relevance of insights provided. Adoption of centralized data definitions and governance practices. Relationships Internal Data Engineering, Data Science, Business Units, Governance Teams External BI platform vendors (Microsoft, Google), consultants, and implementation partners