Senior Data Engineer: Scalable ETL & Real-Time Pipelines

Paracon; Gauteng; Hybrid; ZAR 800,000 - 1,100,000; Full time

Benefits offered by this job

Access courses and conferences

Flexible hybrid work model

Relaxation room and team events

Job summary

A leading technology firm in South Africa, Gauteng is seeking a Senior Data Engineer to join their team. The ideal candidate will have over 7 years of experience developing data ETL pipelines, expertly utilizing Python and SQL, and working with cloud platforms like AWS. Responsibilities include designing data workflows, collaborating with teams, and implementing best practices in data operations. Benefits include a hybrid work model, learning opportunities, and a supportive culture.

Qualifications

• 7+ years of professional experience as a Data Engineer or in a similar role developing data ETL pipelines.
• Advanced proficiency in Python for backend development and scripting.
• Strong SQL skills with hands-on experience in querying and modeling relational databases.

Responsibilities

• Design, develop, test, and maintain reliable data pipelines and ETL processes using Python and SQL.
• Collaborate closely with senior engineers, data scientists, and stakeholders to translate business needs into technical solutions.
• Implement data operations best practices, including automated monitoring, alerting, and incident response for pipeline health.

Skills

Data ETL pipelines

Python

SQL

AWS

Docker

RESTful APIs

CI/CD workflows

Software Development Lifecycle (SDLC)

AI concepts

Tools

Containerization technologies (Docker, Kubernetes)

Infrastructure-as-code tools (Terraform, Helm)

Job description

A leading technology firm in South Africa, Gauteng is seeking a Senior Data Engineer to join their team. The ideal candidate will have over 7 years of experience developing data ETL pipelines, expertly utilizing Python and SQL, and working with cloud platforms like AWS. Responsibilities include designing data workflows, collaborating with teams, and implementing best practices in data operations. Benefits include a hybrid work model, learning opportunities, and a supportive culture.