Standard Bank is a firm believer in technical innovation, to help us guarantee exceptional client service and leading edge financial solutions.
Our growing global success reflects our commitment to the latest solutions, the best people, and a uniquely flexible and vibrant working culture.
To help us drive our success into the future, we are looking for an experienced Data Engineer to join our team at our Johannesburg offices.
Standard Bank is a leading African banking group focused on emerging markets globally. It has been a mainstay of South Africa's financial system for 150 years, and now spans 16 countries across the African continent.
This position is essential in supporting our strategic priority for developing applications of machine learning, artificial intelligence and supporting other strategic priorities such as digitisation.
We aim to grow our internal community of highly skilled and talented professionals.
Key Responsibilities / Accountabilities
Productise data science prototypes
Machine learning engineers sit at the intersection of software engineering and data science and are involved in research, design, experimentation, development, deployment, monitoring, and maintenance.
Design machine learning systems
Design machine learning systems and create intelligent data-driven products using both existing open source libraries & internally developed machine learning models.
Implement machine learning solutions
Develop machine learning applications (production-level code) according to requirements. Software architecture may include platforms such as cloud computing based data platforms or on-premise data platforms.
Research and best practices
Research and implement appropriate frameworks and tools. Contribute to popular open-source machine learning libraries and frameworks where possible.
Keep up to date with current technologies and trends. Help grow our internal machine learning & artificial intelligence community.
Preferred Qualification and Experience
Relevant Tertiary Degree in Quantitative Science
Courses & certifications from reputable academic institutions in Machine Learning or Software Engineering.
IT and Computer Sciences Degree
Certification in MS SQL (including SSRS, SSAS and SSIS)
5-7 Years experience in Engineering - Building databases, warehouses and reporting solutions
5-7 Years experience in Engineering - Building data integration solutions
1- 2 Years experience in Engineering - Operating within an agile team
1- 2 Years experience in Engineering - Working with Risk Management data in Financial Services industry
Knowledge / Technical Skills / Expertise
Experience in data management, data integration and data quality verification
Understanding of Business Intelligence configuration management tools / processes
Background in data profiling
Familiarity with database design and implementation
Experience in troubleshooting, performance tuning, and optimization
Knowledge of CI / CD principles and best practices in data processing
Analytical and problem-solving skills coupled with initiative and accountability
Familiarity with different software development methodologies
Work in conjunction with BI and Data Engineers to ensure high quality Data Deliverable
Design and develop testing frameworks to test ETL jobs, BI reports and Dashboards and other data pipelines
Write SQL scripts to validate data in the data repositories against the data in the source systems
Write SQL scripts to validate data surfacing in BI assets against the data sources
Ensure data quality by checking against our ODS , Data Platforms and the front-end application
Track, monitor and document testing results
The development and maintenance of Extract Transform and Load (ETL) processes, database and performance administration, and dimensional design of the table structure.
Work closely with Data Architect to understanding and operating data warehousing functionality, building the Unified Data Platform in Microsoft Azure cloud
Write high-quality, well-structured code that is maintainable and extensible
Analyze complex data systems to develop automated and reusable solutions for extracting requested information while assuring data validity and integrity
Perform tasks spanning the full lifecycle of data management activities with minimal supervision