Data Engineer – Banking (CIB)
Removed from the employer's board on Nov 2, 2026. First seen by Alion on Oct 31, 2026.
Open roles like this one
Company: BluePearl Consulting
Number of Vacancies: 1
Industry: Banking / Financial Services
Department: Corporate and Investment Banking (CIB)
Contract Duration: 12 months, with potential extension up to 36 months
Expected Start Date: 1 January 2027
Location: Rosebank, Johannesburg, Gauteng
Work Arrangement: Hybrid - approximately 3 days onsite per week
Job Summary
BluePearl Consulting is seeking a strong, experienced Data Engineer to join a software and data engineering team within a Corporate and Investment Banking (CIB) environment.
The successful candidate will specialise in designing, developing and maintaining scalable data pipelines, data integration solutions and cloud-based data platforms. The role requires strong SQL and Python engineering skills, ETL/ELT expertise, data modelling capabilities and hands-on cloud data engineering experience, with AWS as the core platform.
The ideal candidate is a proactive self-starter who takes ownership of deliverables, solves problems independently and maintains high standards of data quality, security and engineering discipline.
Key Responsibilities
Design, develop and maintain scalable ETL/ELT pipelines and data ingestion processes.
Write, optimise and troubleshoot advanced SQL queries, including CTEs and window functions.
Develop reusable Python modules, libraries and automated tests.
Build and maintain relational, dimensional and analytical data models.
Implement data transformations, mappings, validation and reconciliation processes.
Develop and maintain data pipelines using AWS data services.
Implement data orchestration and workflow automation using appropriate tools.
Work with distributed processing technologies such as Spark and PySpark where required.
Support data warehousing, data lakes and lakehouse architectures.
Implement data quality rules, exception handling and source-to-target reconciliation.
Apply data security, access control, encryption and privacy practices.
Implement logging, monitoring, alerting and data observability.
Contribute to Git-based version control, CI/CD and automated deployment pipelines.
Develop and maintain unit, integration, regression and reconciliation tests.
Troubleshoot production incidents, conduct root-cause analysis and support operational recovery.
Maintain technical documentation, data mappings, designs and operational runbooks.
Collaborate with software engineers, data engineers and business stakeholders.
Requirements
Non-Negotiable Requirements
Relevant banking or financial services experience.
Strong hands-on Data Engineering experience.
Advanced SQL engineering, including query optimisation, CTEs, window functions and query plans.
Strong Python engineering, including reusable modules, libraries and testing.
Practical ETL/ELT, data ingestion and transformation experience.
Data modelling experience across relational, dimensional or analytical models.
Cloud data engineering experience, with AWS as the core platform requirement.
Experience with data quality, validation and reconciliation.
Knowledge of data security, access control and privacy.
Familiarity with Git, CI/CD, automated testing and production support.
Strong troubleshooting, problem-solving and technical documentation skills.
Ability to work independently and take ownership of deliverables.
Excellent communication and stakeholder management skills.
Availability to work onsite in Rosebank approximately 3 days per week.
Availability to commence on 1 January 2027.
Core Technical Skills
AWS
Advanced SQL
Python
ETL/ELT
Data ingestion and transformation
Data modelling
Data quality and reconciliation
Data orchestration
Git and CI/CD
Automated testing
Monitoring and production support
Role-Critical Technologies
AWS S3, Glue, Lambda, Athena, Redshift and EMR.
Spark and PySpark.
Kafka and event-driven processing.
Data warehousing, data lakes and lakehouse engineering.
Delta Lake and medallion architecture patterns.
SQS, SNS and EventBridge.
Airflow/MWAA and Step Functions.
Terraform and Infrastructure as Code.
Metadata, data catalogues and lineage.
Performance optimisation, partitioning and query tuning.
Desirable Capabilities
Batch processing and workflow scheduling.
Data governance and data classification.
Cloud cost optimisation and FinOps awareness.
Legacy ETL modernisation and cloud migration.
Data products, interfaces and service-level agreements/objectives.
Data mesh and federated governance.
Core Attributes
Strong banking or financial services awareness.
Self-starter who requires minimal supervision.
Takes ownership of responsibilities and deliverables.
Proactive and analytical problem-solver.
Excellent written and verbal communication.
Strong attention to detail and data quality.
Professional stakeholder engagement.
Smart and professional presentation appropriate to a banking environment.
Recruitment priority: A strong, hands-on Data Engineer with banking experience, advanced SQL and Python capability, AWS expertise and a proven ability to deliver reliable data solutions independently.