Senior Data Engineer: Big Data Pipelines (Hybrid)

Placements24; Gqeberha; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Competitive salary

Medical benefits

Retirement benefits

Professional development

Hybrid work schedule

Job summary

Placements24 is seeking a Senior Data Engineer to join their analytics team in Port Elizabeth. You will design and optimize data pipelines, data warehouses, and data lakes to support BI initiatives and large-scale analytics.

You will work in a hybrid environment with remote flexibility, collaborating with data scientists and analysts to ensure data quality, accessibility, and performance across diverse datasets.

Qualifications

• 5+ years of data engineering or related role with big data exp.
• Proficiency in SQL and programming languages such as Python, Scala or Java.
• Hands-on experience with distributed data processing frameworks (e.g., Spark, Hadoop).
• Experience with cloud data services (AWS Redshift, S3, Azure Data Factory, Google BigQuery).

Responsibilities

• Design, construct, install, and maintain scalable data pipelines and ETL processes.
• Develop and manage large-scale data warehouses and data lakes using big data technologies.
• Ensure data integrity, quality, and security across all data systems.
• Optimize data retrieval and processing for performance and efficiency.
• Collaborate with data scientists and analysts to understand data needs and provide solutions.
• Implement best practices for data governance, data modeling, and data management.

Skills

SQL

Python

Scala

Java

Big Data modeling

Data governance

Education

Bachelor's or Master's in Computer Science or Engineering

Tools

Spark

Hadoop

AWS Redshift

S3

Azure Data Factory

Google BigQuery

Job description

Placements24 is seeking a Senior Data Engineer to join their analytics team in Port Elizabeth. You will design and optimize data pipelines, data warehouses, and data lakes to support BI initiatives and large-scale analytics.

You will work in a hybrid environment with remote flexibility, collaborating with data scientists and analysts to ensure data quality, accessibility, and performance across diverse datasets.