Professional Data Engineer at Rwanda Revenue Authority
Professional Data Engineer

Rwanda Revenue Authority | Type: Job
Published: 2024-11-28 | Deadline: 2024-12-04

Job Title: Professional Data Engineer

Grade: P1

Supervisor: Director for Data Science

Unit Location: HQ

Working Mode: Hybrid

Purpose

A Professional Data Engineer is a technical expert who, under the supervision of Director for Data Science Unit, architects, builds, and maintains an organization's data infrastructure and ecosystem by designing robust data pipelines, implementing automated ETL workflows, ensuring data quality and consistency across systems, supporting cross-divisional data needs with particular focus on Risk Management and Data Analytics, while developing and maintaining data warehouse solutions that align with enterprise risk management frameworks.

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

  • Experience building and optimizing ‘big data’ data pipelines, architectures and data sets
  • Build processes supporting data transformation, data structures, metadata, dependency and workload management
  • SQL and NoSQL databases, including Postgres
  • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
  • Strong analytic skills related to working with unstructured datasets
  • Experience with big data tools: Hadoop, Spark, Kafka, etc
  • Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc

Programming

  • Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc

Project Management

  • Project Management

Risk management

  • Risk management

Software Development

  • Knowledge of best practices and IT operations in an always-up, always-available service
  • CI/CD pipelines
  • Development Excellent problem solving and troubleshooting skills
  • DevOps
  • Advanced Data warehouse and Business Intelligence (Oracle product)

Required Competencies

  • Accountability
  • Client/Citizen Focus
  • Communication
  • Integrity
  • Professionalism
  • Analytical skills
  • Decision making
  • Time management
  • Problem solving
  • Teamwork
  • planning

  • Risk management
  • RRA Business Acumen
  • Ability to maintain accurate records and reporting
  • Flexibility and adaptability
  • Technology awareness
  • Commitment to continuous learning

Required Experiences

  1. 2 years experience in Data Engineering