Business Intelligence Analytics Manager (Project-Based)

Roles & Responsibilities:

• Lead the development and delivery of high-impact BI and Advanced Analytics solutions to solve business problems and pain points, using expertise in functional domain knowledge, data sets, and product solutions.
• Owns Business Intelligence solution Power BI reporting dashboards and perform meaningful quantitative or qualitative analyses addressing impactful business issues or questions.
• Establishing and maintain strong relationships with key stakeholders to ensure that analytics products are aligned with business needs.
• Collaborates with other departments to identify and generate potential Business Intelligence initiatives, that result in business efficiency, cost saving,
• Determine how data can answer challenging business questions, while ensuring data integrity and cleansing processes.
• Working closely with data scientists, engineers, and UX designers to drive product development in a lean/agile environment.

Job Requirements:

• Over 5 years of working experience in data analytics, Business Intelligence, data science and related field
• 3+ years in the lead role engaging with key business stakeholders and IT teams to deliver large scale analytics solutions and projects
• Bachelor's degree in computer science, or a related discipline.
• Familiar with SQL, Azure, SAP Hana and relational databases, able to understand a database schema, how its relationship works. Able to collaborate with Data Engineering and guide Data Analyst to produce data tables, data marts, data sets that meet requirements of business users and reporting needs.
• Hands on Microsoft Power BI, able to produce reporting dashboards that are informative, helpful and user-friendly.
• Demonstrable experience in creating user stories in a Power BI reporting environment.
• Excellent in analytics and problem solving.
• Excellent in communication, presentation, persuasion, and project management.
• Experience in managing and driving outsourced vendors to delivery and operations objectives, managing large-scale data warehouses and data lakes in on-prem and cloud environments with high availability and scalability, and a strong technical knowledge of data integration.

Disclaimer:

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