Senior Business Intelligence

1 week ago

Makati, Philippines UPTC Full time

Qualifications Bachelor’s degree in Information Technology, Computer Science, Data Analytics, Statistics, or a related field. 3–7 years of experience in Business Intelligence, Data Analysis, or Data Warehousing Proficiency using SQL and relational database systems (e.g., SQL Server, PostgreSQL, Oracle). 3 to 7 years experience with BI tools (e.g., Power BI, Tableau, Looker, Qlik). Solid understanding of data modeling (star/snowflake schema), ETL processes, and data architecture concepts. Ability to analyze, interpret, and visualize complex datasets. Strong communication and presentation skills to explain data insights to non-technical stakeholders. Experience with cloud-based data platforms (Azure, AWS, GCP). Experience with ETL tools (SSIS, Talend, or Azure Data Factory). Preferrably has experience or Working knowledge of Python, R, or DAX for data analysis or automation. Understanding of data governance, security, and compliance frameworks. Prior experience in financial services or insurance is an advantage. Job Description The Business Intelligence (BI) Developer is responsible for designing, developing, and maintaining BI solutions that transform organizational data into actionable insights. This role involves developing data models, integrating data from multiple sources, creating dashboards and reports, and ensuring the quality, integrity, and accuracy of the company’s data assets. The BI Developer will collaborate closely with business units — such as Finance, Operations, Sales, and Risk — to deliver data-driven insights that support strategic decision-making. Key Responsibilities Design and develop BI solutions: Create dashboards, visualizations, and reports that support business objectives and KPIs. Develop ETL pipelines: Extract, transform, and load data from various internal and external systems into a centralized data warehouse or BI platform. Data modeling: Build and maintain efficient, scalable data models to support reporting and analytics requirements. Data integration: Collaborate with data engineers and system owners to ensure clean, consistent, and accurate data sources. Performance optimization: Improve query efficiency and data refresh performance across BI systems. Stakeholder engagement: Work closely with business teams to translate business needs into technical BI solutions. Data quality assurance: Validate data accuracy and resolve discrepancies or anomalies. Documentation: Maintain clear documentation for BI processes, data sources, and workflows. Continuous improvement: Stay updated with BI trends, best practices, and emerging technologies. #J-18808-Ljbffr

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