Engineer, Data

Standard Bank Group; Johannesburg; On-site; ZAR 600,000 - 1,000,000; Full time

Job summary

A leading African financial services group seeks a talented Data Engineer for their Johannesburg office. In this role, you will design, implement, and maintain data infrastructure for advanced analytics and machine learning initiatives. Ideal candidates will have a Bachelor's in a related field and over 5 years of data engineering experience, alongside strong programming skills in Python, R, and SQL.

Qualifications

• 5+ years of experience in data engineering or a related field.
• Strong proficiency in programming languages such as Python, R, and SQL.
• Relevant certifications preferred, such as AWS Certified Data Analytics.

Responsibilities

• Develop and maintain scalable data pipelines to collect, process, and store large volumes of data.
• Design and implement ETL processes to transform raw data into meaningful insights.
• Collaborate with data scientists to understand data requirements and implement efficient data models.

Skills

Data Integrity

Data Quality

Programming in Python

Programming in R

SQL

Education

Bachelor's degree in Computer Science, Engineering, Statistics

Tools

Hadoop

Spark

Tableau

Power BI

AWS

Google Cloud

Azure

Job description

Company Description

Standard Bank Group is a leading Africa-focused financial services group, and an innovative player on the global stage, that offers a variety of career-enhancing opportunities – plus the chance to work alongside some of the sector’s most talented, motivated professionals. Our clients range from individuals, to businesses of all sizes, high net worth families and large multinational corporates and institutions. We’re passionate about creating growth in Africa. Bringing true, meaningful value to our clients and the communities we serve and creating a real sense of purpose for you.

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
  
  

Additional Information

Behavioural Competencies:

• Adopting Practical Approaches
• Articulating Information
• Checking Things
• Developing Expertise
• Documenting Facts
• Embracing Change
• Examining Information
• Interpreting Data
• Managing Tasks
• Producing Output
• Taking Action
• Team Working
  
  

Technical Competencies:

• Big Data Frameworks and Tools
• Data Engineering
• Data Integrity
• Data Quality
• IT Knowledge
• Stakeholder Management (IT)