Senior Data Engineer

Placements24; Stellenbosch; Hybrid; ZAR 900,000 - 1,200,000; Full time

Benefits offered by this job

Hybrid work model

Health and wellness benefits

Professional development budget

State-of-the-art data infrastructure

Job summary

Placements24 is seeking a Senior Data Engineer to join the analytics team in Stellenbosch. The role focuses on designing, building, and maintaining data infrastructure to support analytics and BI.

You will own scalable ETL/ELT pipelines, data warehouses, and data lakes, ensuring data quality and accessibility for analysts and data scientists. The position offers a hybrid work model with a strong emphasis on data governance, security, and a data-centric culture.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related quantitative field.
• 5+ years of experience in data engineering, ETL development, or a similar role.
• Strong proficiency in SQL and experience with relational and NoSQL databases.
• Hands-on experience with big data technologies (e.g., Spark, Hadoop) and cloud data platforms (AWS Redshift, Azure Data Lake, GCP BigQuery).
• Proficiency in programming languages like Python or Scala for data manipulation and pipeline development.
• Experience with data warehousing concepts and dimensional modeling.

Responsibilities

• Design, develop, and optimize scalable ETL/ELT pipelines to ingest and transform data from diverse sources.
• Build and maintain data warehouses and data lakes using modern technologies.
• Ensure data quality, integrity, and availability across all data systems.
• Collaborate with data scientists and analysts to understand their data needs and provide efficient access.
• Implement data governance and security best practices.
• Automate data processes and monitor pipeline performance for efficiency and reliability.

Skills

SQL

Python

Scala

Data warehousing concepts

Relational and NoSQL databases

Education

Bachelor's degree in Computer Science or Engineering

Tools

Spark

Hadoop

AWS Redshift

Azure Data Lake

GCP BigQuery

Job description

About the Role

Our client is seeking a seasoned Senior Data Engineer to join their analytics team in Stellenbosch. This hybrid role is essential for designing, building, and maintaining our data infrastructure, ensuring reliable and efficient data pipelines for analytics and business intelligence. You will work with large volumes of data, implementing robust ETL/ELT processes and optimizing data warehousing solutions. Collaborating with data scientists and analysts, you will enable data-driven decision-making across the organization. This is an excellent opportunity to shape data strategy and contribute to a data-centric culture within a renowned institution.

Key Responsibilities

• Design, develop, and optimize scalable ETL/ELT pipelines to ingest and transform data from diverse sources.
• Build and maintain data warehouses and data lakes using modern technologies.
• Ensure data quality, integrity, and availability across all data systems.
• Collaborate with data scientists and analysts to understand their data needs and provide efficient access.
• Implement data governance and security best practices.
• Automate data processes and monitor pipeline performance for efficiency and reliability.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related quantitative field.
• 5+ years of experience in data engineering, ETL development, or a similar role.
• Strong proficiency in SQL and experience with relational and NoSQL databases.
• Hands-on experience with big data technologies (e.g., Spark, Hadoop) and cloud data platforms (AWS Redshift, Azure Data Lake, GCP BigQuery).
• Proficiency in programming languages like Python or Scala for data manipulation and pipeline development.
• Experience with data warehousing concepts and dimensional modeling.

Benefits

• Competitive annual salary with performance-related bonuses.
• Hybrid work model providing flexibility with a base in Stellenbosch.
• Comprehensive health and wellness benefits package.
• Generous allocation for professional development and certifications.
• A collaborative environment focused on innovation and data excellence.
• Access to state-of-the-art data infrastructure and tools.