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Engineer

2 months ago

Cape Town, South Africa Gijima Holdings Full time
Introduction:Are you an innovative thinker with a passion for designing and implementing scalable processes? Our client is looking for an Engineer responsible for creating robust data processes, developing a data platform, implementing cloud solutions, supporting DevOps practices, applying machine learning techniques, and creating data visualizations.

Minimum Requirements:
  • Education Background:
    • Bachelors degree in Computer Science, Business Informatics, Mathematics, Statistics, Engineering, or a related field.
  • Professional Experience:
    • 4-5 years of relevant engineering experience.
Technical Skills:
  • Strong understanding of data structures, algorithms, and software design.
  • Experience with structured and unstructured data, different data stores, and traditional RDBMS and data warehouses.
  • Proficiency in programming languages such as Python, Scala, Java, and C.
  • Practical experience with Apache Spark and cloud services (e.g., AWS, Azure, GCP).
  • Experience with version control systems like Git and SVN.
  • Proficiency in data visualization tools such as PowerBI, QuickSight, and QlikSense.
  • Experience with DevOps practices, including CI/CD and Infrastructure as Code.
Specialized Skills:
  • Data Engineering:
    • Experience with big data, ETL, and data management processes.
  • Platform Engineering:
    • Experience with cloud platform development and maintenance.
  • Cloud Engineering:
    • Experience with cloud architecture and API development.
  • DevOps:
    • Experience with DevOps practices, architecture, and operation.
  • ML Engineering:
    • Experience with machine learning frameworks and model integration.
  • Data Visualization:
    • Experience with data visualization tools and techniques.
Job Description:
  • Data Process Design and Implementation:
    • Design and implement scalable processes for ingesting and transforming large data sets.
    • Develop and maintain data platforms and deploy cloud solutions.
  • Data Pipeline Management:
    • Design, implement, and maintain data pipelines for large, complex data sets from various sources
  • Cloud Strategy Implementation:
    • Align cloud strategies with data architecture, security, and governance requirements.
  • DevOps Practices:
    • Enhance efficiency and automation through DevOps practices, including infrastructure and solutions as code.
  • Machine Learning Integration:
    • Integrate machine learning models into data processes and the ML platform.
  • Data Visualization
    • Design processes for visualizing large data sets, enabling self-service visualization and analytics.
  • API Development:
    • Develop APIs to expose data to enterprise applications and third-party vendors.
  • Stakeholder Collaboration:
    • Work with various stakeholders to understand data requirements and apply technical knowledge to solve key business problems.
  • Operational Support:
    • Provide support in the operational environment with all relevant support teams for data services.