Data Engineer at Paracon

About the job

Working for our client is more than just a job. They really pull out all the stops when it comes to supporting the people who work for them, be it with their beautiful, state of the art offices or their development opportunities. Their people are passionate and their dedication is unparalleled.

They are actively looking for a Data Engineer to join their cross-functional Data Science team in Cape Town.

You will be responsible for developing and maintaining robust data pipelines capable of handling terabytes of data as well as performing complex data analyses and building predictive models.

To apply, you need to have a relevant Degree (with an outstanding academic record) combined with a minimum of 2 years’ practical working experience in a similar role. You need to come from a Computer Science or similar background to succeed in this role.

Your skills/experience must include:

• Experience in a language with a large data-science community (Python or R);
• Knowledge of commonsoftware architectures and development patterns and practices (Microservices, SOLID);
• Knowledge of thesoftware development lifecycle (Scrum or Kanban) from initial specifications to maintenance and support;
• Backend development (APIs, messaging, multithreaded systems, scheduling); and,
• Basic familiarity with DevOps concepts (Infrastructure-as-code, CI/CD).

*This is not an entry-level position, but rather than looking for specified years’ experience, we are interested in how you can demonstrate your innovative use of these technologies to solve complex data problems.

Experience with the following will be preferred and set you above the rest:

• Domain knowledge in asset management;
• Cloud-based infrastructure and services (AWS, Azure, GCP);
• Continuous integration/deployment workflows and tools (Gitlab);
• SQL & NoSQL database development (SQL Server, MongoDB);
• Containers and container orchestration (Docker, Kubernetes);
• Cluster computing frameworks (Spark, Hadoop);
• Business intelligence tools (PowerBI, Qlik);
• Data manipulation frameworks (Pandas in Python);
• Machine-learning frameworks (TensorFlow, scikit-learn);
• Data visualization (plotly, matplotlib);
• Modern web development (React, Angular, or similar);
• Automated testing (Unit testing and higher-level test frameworks).