Data Architect Specialist

7 days ago


Sandton, South Africa Innovation Group Full time

Job Description



The Senior Data Engineer will be responsible for developing and implementing data warehousing blueprints, evaluating hardware and software platforms, and integrating systems. This individual must have a deep understanding of data design, database architecture, metadata, and repository creation.



Responsibilities


  • Develop and implement data warehousing blueprints
  • Evaluate hardware and software platforms
  • Integrate systems
  • Manage the data environment
  • Translate business needs into long-term architecture solutions
  • Define, design, and build dimensional databases
  • Evaluate re-usability of current data for additional analyses
  • Conduct data cleaning to rid the system of old, unused, or duplicate data
  • Review data models and the metadata repository to structure the data for better management and quicker access


Requirements

To be successful in this role, you will need:




  • Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field
  • Relevant certifications in cloud platforms (e.g., AWS Certified Data Analytics, Google Professional Data Engineer)
  • Certifications in data engineering or big data technologies
  • Experience in handling and processing large datasets efficiently
  • Understanding of cloud architecture and best practices for deploying data solutions
  • Experience in managing data projects using agile practices (e.g., Scrum, Kanban)


Preferred Qualifications

If you have any of the following qualifications, it would be a plus:




  • Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field (Master's degree preferred)
  • Familiarity with big data frameworks such as Apache Hadoop, Spark, and Kafka
  • Knowledge of relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra)
  • Expertise in designing scalable and efficient data architectures that support large-scale data processing
  • Understanding of data modeling techniques, including dimensional and normalized models
  • Experience in managing data projects using agile practices (e.g., Scrum, Kanban)

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