Data Engineer

Job Description

• We are seeking a skilled Data Engineer to support the design, development, and maintenance of scalable data solutions within a banking environment.
• The role will focus on building reliable data pipelines, integrating data from multiple sources, supporting analytics and reporting, and ensuring data is accurate, secure, and available for business decision-making.

What you'll do:

• Design, build, test, and maintain data pipelines and ETL/ELT processes.
• Extract, transform, and load data from multiple source systems.
• Work with data scientists, analysts, BI developers, architects, and business stakeholders.
• Develop and optimise SQL queries, stored procedures, and data transformation logic.
• Support data integration between operational systems, data warehouses, lakes, and reporting platforms.
• Build and maintain data models to support analytics, reporting, and downstream consumption.
• Monitor data pipelines for failures, performance issues, and data quality concerns.
• Troubleshoot and resolve data-related production issues.
• Support data governance, security, access control, and compliance requirements.
• Document data flows, data definitions, technical designs, and support procedures.
• Contribute to automation, performance optimisation, and continuous improvement of the data platform.
• Support data analysis requirements to enable business insights and decision-making.

Your Expertise:

• 3+ years’ experience as a Data Engineer, BI Data Engineer, ETL Developer, Data Warehouse Developer, or similar.
• Strong hands-on experience with SQL.
• Experience building and maintaining ETL/ELT pipelines.
• Experience working with large datasets and multiple source systems.
• Experience with data warehousing, data lakes, or lakehouse environments.
• Experience with tools such as Azure Data Factory, Databricks, Synapse, Microsoft Fabric, AWS Glue, Redshift, BigQuery, Snowflake, or similar would be advantageous.
• Experience with Python, PySpark, Spark, Scala, or similar would be beneficial.
• Understanding of data modelling, dimensional modelling, and data transformation principles.
• Experience with data analysis, data exploration, and supporting analytical use cases.
• Experience with data quality checks, reconciliation, and pipeline monitoring.
• Banking, fintech, payments, risk, fraud, customer analytics, or financial services experience would be advantageous.

Technical Skills

• SQL / T-SQL
• Data Analysis
• ETL / ELT
• Data pipelines
• Data warehousing
• Data lakes / lakehouse
• Data modelling
• Python / PySpark
• Spark / Databricks
• Azure Data Factory
• Azure Synapse
• Microsoft Fabric
• Snowflake
• BigQuery / Redshift
• APIs / file ingestion
• Git / CI/CD
• Data quality
• Data governance
• Power BI integration

Other information applicable to the opportunity:

• Contract position
• Location: Johannesburg (Hybrid)