2 Job Positions of Professional in Charge of Data Collection and Management at RRA: Deadline:3 Apr 2023

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Purpose
A Professional in charge of data collection and management is the principal technical expert in Data Engineering Section. Under the supervision of Supervisor in charge of Data Engineering Section, the professional in charge of data collection and management extracts data from systems and submits the data to other teams in Risk Management and Data Analytics Division for analysis, develops and reviews risk rules in Data warehouse.
Key duties and responsibilities
  1. Build, test, and maintain database pipeline architectures
  2. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of RRA data sources using SQL and AWS ‘big data’ technologies
  3. Create data tools for analytics and data scientist team members that assist them in building and optimizing product into an innovative industry leader
  4. Develops and maintains scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity
  5. Collaborates with data science and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organ
  6. Identify or define data sources required in risk management and data analytics division or other useful information from data warehouse and other relevant information systems
  7. Extract internal and external data to be used by teams in risk management and data analytics division for risk analysis
  8. Develop and review risk rules in Data warehouse
  9. Develop and review the electronic risk register
  10. Develop the Risk Differentiation Frameworks (RDFs) in the system
  11. Carry out any other task assigned by the supervisor
Required Academic Qualification
   Preferred Qualifications
  1. Master’s Degree in Information Technology specialized in Information Technology
  2. Master’s Degree in Computer Science specialized in Computer Science
  3. Master’s Degree in Computer Engineering specialized in Computer Engineering
  4. Master’s Degree in Electrical and Computer Engineering specialized in Electrical and Computer Engineering
   Relevant Qualifications
Skill Type Required Skill Required Proficiency level
Data Management Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases advanced
Data Management Strong analytic skills related to working with unstructured datasets advanced
Data Management Experience with big data tools: Hadoop, Spark, Kafka, etc advanced
Data Management Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc advanced
Data Management Experience building and optimizing ‘big data’ data pipelines, architectures and data sets advanced
Data Management Build processes supporting data transformation, data structures, metadata, dependency and workload management advanced
Data Management SQL and NoSQL databases, including Postgres advanced
Programming Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc advanced
Project Management Project Management advanced
Risk management Risk management advanced
Software Development Excellent problem solving and troubleshooting skills advanced
Software Development DevOps advanced
Software Development Advanced Data warehouse and Business Intelligence (Oracle product) advanced
Software Development Knowledge of best practices and IT operations in an always-up, always-available service advanced
Software Development CI/CD pipelines advanced
Required Competencies
  1. Accountability
  2. Client/Citizen Focus
  3. Communication
  4. Integrity
  5. Professionalism
  6. Analytical skills
  7. Decision making
  8. Time management


  9. Problem solving
  10. Teamwork
  11. planning
  12. Risk management
  13. RRA Business Acumen
  14. Ability to maintain accurate records and reporting
  15. Flexibility and adaptability
  16. Technology awareness
  17. Commitment to continuous learning
Required Experiences
  1. 2 years experience in Data Engineering

 

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