Senior data engineer

About the Role

Our client is seeking a skilled and analytical Senior Data Engineer to join their growing data team in Port Elizabeth. In this hybrid role, you will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure that support business intelligence, analytics, and machine learning initiatives. You will work with large datasets, transforming raw data into actionable insights. This position is perfect for a data professional who enjoys working with complex data challenges, collaborating with stakeholders, and contributing to data-driven decision-making in a flexible hybrid work model.

Key Responsibilities Design, construct, install, test, and maintain highly scalable data management systems and pipelines. Develop and maintain ETL/ELT processes to ingest, transform, and load data from various sources. Build and optimize data warehouses, data lakes, and other data storage solutions. Collaborate with data scientists, analysts, and business stakeholders to understand their data needs and deliver solutions. Ensure data quality, integrity, and security across all data platforms. Monitor data systems performance and troubleshoot issues to ensure efficient data flow and availability. Requirements Bachelor's degree in Computer Science, Engineering, Statistics, or a related quantitative field. Minimum of 5 years of experience in data engineering or a related role. Strong programming skills in SQL and at least one scripting language (e.g., Python, Scala, Java). Proven experience with big data technologies (e.g., Spark, Hadoop, Kafka) and cloud data services (AWS, Azure, GCP). Expertise in designing and implementing data warehousing solutions and dimensional modeling. Familiarity with data visualization tools and BI platforms is a plus. Benefits Competitive salary package with performance-based incentives. Hybrid work arrangement offering a balance between remote work and office collaboration. Comprehensive medical, dental, and vision insurance. Opportunities for professional development and continuous learning in data technologies. A data-centric culture that values insights and innovation.