Data Engineer

Job Title : Data Engineer

Location : Johannesburg

Job Type : Contract (8-month contract)

Work Arrangement : Hybrid

Our client is looking for a skilled Data Engineer to join the team on a contract basis, working within a dynamic and fast-paced banking / financial services environment.

The ideal candidate will have solid experience in designing and building robust data pipelines and architectures to support advanced analytics, reporting, and data-driven decision-making.

Key Responsibilities

1. Design, develop, and maintain scalable and efficient data pipelines and ETL processes.
2. Ingest, transform, and load data from various internal and external sources into data warehouses or data lakes.
3. Ensure data quality, integrity, and consistency across all systems and processes.
4. Collaborate with business stakeholders, data analysts, and BI teams to understand data requirements and deliver appropriate solutions.
5. Implement data solutions that comply with governance, regulatory, and security standards.
6. Perform root cause analysis on internal and external data and processes to answer specific business questions.
7. Monitor and troubleshoot data pipeline issues and performance bottlenecks.
8. Document data flow processes and contribute to maintaining best practices for data engineering across the team.

Experience and Qualifications

1. Bachelor's degree in computer science, Information Systems, Engineering, or a related field.
2. 3-5+ years of proven experience as a Data Engineer in a banking or financial services environment.
3. Relevant certifications in data engineering, cloud platforms, or database management are advantageous.
4. Strong proficiency in SQL and experience with large-scale data systems.
5. Hands-on experience with ETL tools and frameworks (e.g., Apache NiFi, Talend, SSIS).
6. Experience with cloud platforms such as Azure (preferred), AWS, or GCP.
7. Proficiency with Azure Data Factory, Synapse Analytics, and Data Lake solutions.
8. Solid experience with Python or Scala for data processing.
9. Familiarity with big data tools such as Databricks, Spark, or Kafka.
10. Exposure to CI / CD tools and DevOps practices for data pipelines.
11. Strong understanding of data modelling, data warehousing, and data governance principles.
12. Knowledge of APIs and integrating data from multiple source systems.

Join us in shaping the future of client solutions!

If you're ready to take on a new challenge and make an impact, we want to hear from you.

Apply now!