Data Engineer - AWS

SUMMARY:
Psybergate is an IT company that builds bespoke software solutions and provides highly skilled resources to its clients.
We are looking for a Senior Data Engineer - AWS to join our financial services client based in Centurion.
 
The Senior Data Engineer is responsible for designing, building, and maintaining robust, scalable data pipelines and platforms to support advanced analytics, BI, and data-driven decision-making. This individual brings strong technical experience, shows leadership in data initiatives, and works closely with both technical and business stakeholders to ensure high-quality data solutions.

POSITION INFO:
What you will be doing: 

• Design, develop and maintain complex data pipelines from multiple sources into a central data platform/lakehouse.
• Ensure reliability, scalability, and maintainability of pipelines.
• Optimize data flows and data quality checks.
• Contribute to the architectural design and enhancements of the data platform.
• Support the implementation of cloud-first data solutions, primarily in AWS.
• Lead initiatives for automation, monitoring, and CI/CD for data engineering workflows.
• Provide technical guidance and mentorship to Data Engineers.
• Advocate for best practices in data engineering, including version control, testing, and documentation.
• Conduct code reviews and support knowledge sharing across the team.
• Collaborate with data scientists, analysts, software engineers, and business stakeholders.
• Translate business requirements into technical specifications and deliverables.
• Support data consumers by developing reports, data products, and self-service solutions.
• Keep up to date with new tools, technologies, and best practices in data engineering.
• Evaluate and integrate new data sources and technologies as required.
• Champion a data-driven culture within the organisation.

• Completed degree or diploma in Computer Science, Information Systems, Engineering, or a related field.
• 4 – 7 years of hands-on data engineering experience.
• Advanced proficiency in Python and SQL.
• Strong database design knowledge and experience with data warehousing techniques and modelling approaches.
• Experience building and maintaining cloud-based data architecture (AWS preferred).
• Hands-on experience with data ingestion from, amongst others: Microsoft SQL Server, Oracle, MongoDB, Amazon S3 and other AWS data services, HTTP APIs, SFTP, and various file systems.
• Proficiency with Git, CI/CD pipelines, and Agile methodologies.
• Familiarity with machine learning workflows and supporting analytics teams.
• Strong experience with BI tools like Power BI for data storytelling.