Engineer, Data - Johannesburg, 5 Simmonds Street at Standard Bank Group

Job Description

• We are seeking a talented Data Engineer to join our team in Johannesburg, South Africa. As a Data Engineer, you will play a crucial role in designing, implementing, and maintaining our data infrastructure to support advanced analytics and machine learning initiatives.
• Develop and maintain scalable data pipelines to collect, process, and store large volumes of data
• Collaborate with data scientists and analysts to understand data requirements and implement efficient data models
• Design and implement ETL processes to transform raw data into meaningful insights
• Optimize data systems for performance, reliability, and scalability
• Implement data quality checks and monitoring systems to ensure data integrity
• Develop and maintain documentation for data processes and architectures
• Stay up-to-date with emerging technologies and best practices in data engineering
• Participate in code reviews and contribute to the improvement of our data engineering practices

Qualifications

• Bachelor's degree in Computer Science, Engineering, Statistics, or a related field
• 5+ years of experience in data engineering or a related field
• Strong proficiency in programming languages such as Python, R, and SQL
• Experience with big data technologies like Hadoop and Spark
• Knowledge of machine learning algorithms and statistical modeling techniques
• Familiarity with data visualization tools such as Tableau or Power BI
• Excellent problem-solving skills and attention to detail
• Strong analytical and organizational abilities
• Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) is a plus
• Understanding of data privacy and security practices
• Knowledge of data governance principles
• Relevant certifications (e.g., AWS Certified Data Analytics, Google Cloud Professional Data Engineer) are preferred
• Ability to work efficiently in a fast-paced, collaborative environment
• Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders