Data Engineer

Job Opportunity: Database & AI / ML Engineer (Dual-Purpose Role)

We are seeking an experienced Database & AI / ML Engineer. In this dual-purpose role, you will be at the forefront of shaping our AI strategy and building innovative AI products from scratch.

You will play a crucial part in both database engineering and AI / ML development, ensuring that our systems are optimized, robust, and scalable.

Key Responsibilities:

1. Assist with AI development and production infrastructure.
2. Help business stakeholders understand the potential and limitations of AI.
3. Build AI models and deploy them into production.
4. Develop machine learning systems, forecasting algorithms, and analytics tools.
5. Convert AI / ML models into APIs for operational use.
6. Manage data science prototypes and select datasets for AI models.
7. Build data ingest and transformation infrastructure.
8. Maintain database integrity, optimize performance, and ensure fast query execution.
9. Design, implement, and troubleshoot ETL (Extract, Transform, Load) processes.
10. Engage in database warehouse design, development, and reporting.
11. Collaborate with stakeholders and developers to implement efficient data solutions.

Skills & Competencies:

1. Creative, decisive, and a strong problem-solver.
2. Ability to work independently and within a team.
3. Strong work ethic and attention to detail.
4. Proficient in Python, SQL, and other AI / ML technologies.
5. Experience with tools such as TensorFlow, PyTorch, Mlflow, NumPy, and GPT-3 (OpenAI).
6. Knowledge of relational databases, data architecture, and database optimization.
7. Familiarity with tools like Microsoft Visio, Erwin Data Modeler, and business intelligence software.

Qualifications:

1. Matric or equivalent qualification.
2. Bachelor's degree in Computer Science, Data Science, Software Development, or a related field (Master's preferred).
3. At least 5 years of experience in big data, database management, and API development.
4. Expertise in PostgreSQL, SQL, and data integration tools.
5. Experience in machine learning algorithms and the use of deep learning frameworks.
6. Strong presentation and communication skills.