Senior Data Engineer

Sabenza IT & Recruitment; Centurion; On-site; ZAR 900,000 - 1,400,000; Full time

Job summary

Sabenza IT & Recruitment seeks a data engineer to own ingestion, transformations, checks and governance for a retail investments technology team in Centurion. You will build and operate data pipelines, enable analytics and BI, and set technical direction for the platform.

You will work in an Agile environment, design efficient pipelines, coach junior engineers, and ensure data quality, security and governance across the stack.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering or a related field. A relevant certification helps.
• 4–7+ years in data engineering, with production pipelines and platforms you can talk through.
• Advanced Python and SQL.
• Data modelling, analytics-oriented schema design and warehousing.
• Ingestion from relational databases, cloud storage, APIs and files.
• Git, CI/CD and automation. Agile or SAFe delivery.
• You have used AI in engineering work and you know how to check it.
• Power BI or a similar BI tool is useful.
• You can explain a constraint to a business stakeholder and a design choice to another engineer.

Responsibilities

• Deliver data engineering work inside an Agile team. Plan it, estimate it, break features into tasks, and hit the quality bar you agreed with the product owner.
• Design and build ingestion and transformation pipelines across systems and domains. Batch and incremental. Error handling, monitoring, alerting, validation and reconciliation included.
• Shape solutions that fit the target data platform. The environment is cloud and AWS-aligned. You will be expected to call the cost, security, performance and support impact of a design before it is built.
• Coach less experienced data engineers. Give analytics, BI and data science a clear view of structures, availability and how a pipeline actually behaves.
• Review code and configuration. Simplify what is already there. Use Git, automated testing, CI/CD and structured releases. Document enough that someone else can support it.
• Use AI in the engineering workflow, on approved tools only. You validate the output. You do not put client or proprietary data into a public model. You stay accountable for what goes to production.
• Join incident response and root-cause work when a pipeline fails, and build privacy, access control and regulatory requirements in from the start.

Skills

Python

SQL

Data modelling

Analytical thinking

Education

Bachelor’s degree in Computer Science or related field

Tools

Git

CI/CD

AWS

Power BI

Job description

Centurion, South Africa | Posted on 28/10/2026

The reporting is only as good as the pipelineunderneath it. This role owns that layer: the ingestion, the transformations,the checks, and the support when a number downstream does not match.

It is a permanent seat in Centurion, in a retailinvestments technology team, reporting to the Head of Application Development.You will build and run data pipelines and the platform they sit on, soanalytics, BI and the business get data they can trust. You will also settechnical direction in the team. That means design calls, engineeringstandards, and how AI is used in the work without breaking governance.

What you will do

• Deliver data engineering work inside an Agile team. Plan it,estimate it, break features into tasks, and hit the quality bar you agreedwith the product owner.
• Design and build ingestion and transformation pipelines acrosssystems and domains. Batch and incremental. Error handling, monitoring,alerting, validation and reconciliation included.
• Shape solutions that fit the target data platform. Theenvironment is cloud and AWS-aligned. You will be expected to call thecost, security, performance and support impact of a design before it isbuilt.
• Coach less experienced data engineers. Give analytics, BI anddata science a clear view of structures, availability and how a pipelineactually behaves.
• Review code and configuration. Simplify what is already there.Use Git, automated testing, CI/CD and structured releases. Document enoughthat someone else can support it.
• Use AI in the engineering workflow, on approved tools only. Youvalidate the output. You do not put client or proprietary data into apublic model. You stay accountable for what goes to production.
• Join incident response and root-cause work when a pipeline fails,and build privacy, access control and regulatory requirements in from thestart.

Requirements

hatyou need

• Abachelor’s degree in Computer Science, Information Systems, Engineering ora related field. A relevant certification helps.
• 4–7+ yearsin data engineering, with production pipelines and platforms you can talkthrough.
• AdvancedPython and SQL.
• Datamodelling, analytics-oriented schema design and warehousing.
• Ingestionfrom relational databases, cloud storage, APIs and files.
• Git, CI/CDand automation. Agile or SAFe delivery.
• You haveused AI in engineering work and you know how to check it.
• Power BIor a similar BI tool is useful.
• You canexplain a constraint to a business stakeholder and a design choice toanother engineer.