Senior Azure Databricks Data Engineer (Hybrid)

Confluent; Cape Town; Hybrid; ZAR 650,000 - 900,000; Full time

Benefits offered by this job

Medical aid

Retirement annuity

Bursaries and Insurance

Job summary

Confluent Services, South Africa’s leading debt management company, seeks a Data Engineer to design, build, and maintain data pipelines across on‑prem and cloud platforms. You’ll work with Azure Databricks and Data Factory within a growing Data Team, influencing architecture and data workflows.

You will collaborate with analysts, data scientists, and stakeholders to ensure data quality and enable analytics and ML initiatives.

Qualifications

• Bachelor's degree in CS/Engineering or related field.
• Minimum 3 years as a data engineer or similar role.
• Experience with Azure services (ADF, Databricks) preferred.
• Knowledge of SQL Server and Azure Data Lake Storage.
• Strong communication and teamwork abilities.
• Attention to detail and data problem-solving skills.

Responsibilities

• Contribute to architecture and design of the Confluent Data Platform.
• Develop and support scalable data pipelines on Azure.
• Ensure data quality, security and integrity across pipelines.
• Collaborate with data product owners, analysts and scientists.
• Assist in data initiatives and support technical teams.

Skills

Data pipelines

ETL processes

Azure

Azure Data Factory

Azure Databricks

SQL

Data Lake

Teamwork

Attention to detail

Problem solving

Education

Bachelor's degree in Computer Science or Engineering

Tools

Azure

Azure Data Factory

Azure Databricks

Microsoft Fabric Data Engineering

SQL Server / Data Lake Storage

Job description

Confluent Services, South Africa’s leading debt management company, seeks a Data Engineer to design, build, and maintain data pipelines across on‑prem and cloud platforms. You’ll work with Azure Databricks and Data Factory within a growing Data Team, influencing architecture and data workflows.

You will collaborate with analysts, data scientists, and stakeholders to ensure data quality and enable analytics and ML initiatives.