Business Intelligence Infrastructure Specialist Under Statute at RWANDA INFORMATION SOCIETY AUTHORITY (RISA): (Deadline 20 October 2022)
Job description
• Responsible for the design, development, implementation, management and support of mission critical enterprise BI reporting and Extract, Transform, Load (ETL) processes and environments.
• Business analysis to gather required BI system requirements
• Translate business requirements into specifications that will be used to drive data store/ data warehouse/ data mart design and configuration
• Develop BI reports utilizing advanced data visualization techniques and related ETL tools to load data store(s)/ data warehouse(s)/ data mart(s), SQL with overall responsibility for implementation and support.
• Write SQL to explore source data, data issues, etc.
• Identify impact on existing model/ solution triggered by new/changed requirements
• Presenting the valuable insights generated from complex data set analysis through visualization techniques
• Establishing scorecards and dashboards with process performance metrics, targets and triggers
• Assist in issue identification, investigation, ownership, communication and resolution process for Analytical Models
• Participate in system architecture design and tool set selection.
• Provide support as required to ensure the availability and performance of enterprise data and BI environments for both external and internal users
Minimum Qualifications
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Advance Diploma in Information Management
3 Years of relevant experience
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Bachelor’s Degree in Information Management
3 Years of relevant experience
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Advanced diploma in Computer Science
3 Years of relevant experience
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Advanced diploma in Computer Engineering
3 Years of relevant experience
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Advanced diploma in Information and Communication Technology
3 Years of relevant experience
-
Advanced diploma in Electronics and Telecommunication Engineering
3 Years of relevant experience
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Bachelor’s Degree in Computer Science
3 Years of relevant experience
-
Bachelor’s Degree in Computer Engineering
3 Years of relevant experience
-
Bachelor’s Degree in Information and Communication Technology
3 Years of relevant experience
-
Bachelor’s Degree in Electronics and Telecommunication Engineering
3 Years of relevant experience
-
Master’s Degree in Computer Science
1 Year of relevant experience
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Master’s Degree in Computer Engineering
1 Year of relevant experience
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Master’s Degree in Information and Communication Technology
1 Year of relevant experience
-
Master’s Degree in Data Sciences
1 Year of relevant experience
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Bachelor’s Degree in Data Sciences
3 Years of relevant experience
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Bachelor’s Degree in Information Systems
3 Years of relevant experience
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Master’s Degree in Information Systems
1 Year of relevant experience
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Master’s Degree in Information Management
1 Year of relevant experience
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Bachelor’s Degree in Business Information Technology
3 Years of relevant experience
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Data Sciences
3 Years of relevant experience
-
Master’s Degree in Electronics and Telecommunication Engineering
1 Year of relevant experience
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Advanced diploma ( A1) in Business Information Technology
3 Years of relevant experience
-
Master’s Degree in Business Information Technology
1 Year of relevant experience
-
Advanced diploma in Information System
3 Years of relevant experience
Competency and Key Technical Skills
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N/A
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Strong critical thinking skills and excellent problem solving skills.
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Inclusiveness
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Accountability
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Communication
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Teamwork
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Client/citizen focus
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Professionalism
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Commitment to continuous learning
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Resource management skills
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Analytical skills
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Problem solving skills
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Decision making skills
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Time management skills
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Risk management skills
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Results oriented
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Digital literacy skills
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Fluency in Kinyarwanda, English and/ or French. Knowledge of all is an added advantage
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Experience with database queries, stored procedure writing, Online Analytical Processing (OLAP), data cube technology, CRM platforms, BI and relevant tools;
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Knowledge of GIS, Business Intelligence, Big Data, Data Warehouse, ETL, Data modeling, reporting and analytics;
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Appreciation of data lakes, data warehouses and the use of Extract Transform and Load (ETL) pipeline concepts;
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