Engineer, Data (Corporate & Investment Banking)

Job Overview

Business Segment: Corporate & Investment Banking

Location: ZA, GP, Johannesburg, 30 Baker Street

To develop and maintain complete data architecture across several application platforms, provide capability across application platforms. To design, build, operationalise, secure and monitor data pipelines and data stores to applicable architecture, solution designs, standards, policies and governance requirements thus making data accessible for the evaluation and optimisation for downstream use case consumption. To execute data engineering duties according to standards, frameworks, and roadmaps

• Acquire datasets that align with business needs and requirements to enable useful and actionable information, providing feedback on the clarity and completeness of data requirements. Analyse data elements and systems, data flow, dependencies,and relationships to ensure conceptual physical and logical data models.
• Apply subject matter expertise into decisions relating to data engineering and data integration. Educate internal stakeholders on data engineering and data integration perspectives on new approaches.
• Build required infrastructure for optimal extraction, transformation and loading of data from various data sources using various technologies (i.e. AWS and SQL technologies). Build, create, manage, and optimise data pipelines, move data pipelines into production, enabling data consumers to utilise data for reporting purposes.
• Collaborate with insights teams, Technology engineers and Data & Analytics leadership to identify opportunities for process improvements, recommend system modifications and give input to the development of policies for data governance.
• Contribute to automation initiatives and guide the identification, design, and implementation of internal process improvements,

• Degree (Business Commerce/Information Studies (Min)

Experience Required: Software Engineering

5-7 years: Experience in building databases, warehouses, reporting and data integration solutions. Experience building and optimising big data data-pipelines, architectures and data sets. Experience in creating and integrating APIs. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement

8-10 years: Deep understanding of data pipelining and performance optimisation, data principles, how data fits in an organisation, including customers, products and transactional information. Knowledge of integration patterns, styles, protocols and systems theory

8-10 years: Experience in database programming languages including SQL, PL/SQL, SPARK and or appropriate data tooling. Experience with data pipeline and workflow management tools