Data Engineer – Banking (CIB)

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.