Data Engineer
Summary
Design, build, and maintain scalable data pipelines, warehouses, and ETL processes for an energy-sector leader in Richards Bay, KwaZulu-Natal, supporting analytics, BI, and machine learning. Core stack: SQL, Python/Java, big data tools (Hadoop, Spark, Kafka), and cloud data services (AWS, Azure, GCP). Hybrid work model.
About the Role Our client, a prominent leader in the energy sector, is seeking a skilled Data Engineer to join their analytical team in **Richards Bay, KwaZulu-Natal**. This hybrid role offers the unique opportunity to work on complex data challenges within a critical industry, balancing on-site collaboration with remote flexibility. You will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure that support advanced analytics, business intelligence, and machine learning initiatives. The ideal candidate will possess strong programming skills, extensive experience with big data technologies, and a deep understanding of data warehousing and ETL processes. You will work closely with data scientists, analysts, and business stakeholders to ensure data is accessible, reliable, and optimized for analysis. Join a company committed to innovation and sustainability, where your contributions will directly impact strategic decision-making and operational efficiency. This position is based in **Richards Bay**.
Key Responsibilities
- Design, construct, install, test, and maintain highly scalable data management systems and data pipelines.
- Develop and implement ETL (Extract, Transform, Load) processes to integrate data from various sources.
- Build and optimize data warehouses and data lakes for efficient data storage and retrieval.
- Collaborate with data scientists and analysts to understand their data needs and provide clean, well-structured datasets.
- Ensure data quality, integrity, and reliability across all data platforms.
- Monitor data pipeline performance and troubleshoot any issues that arise.
- Implement data security and compliance measures.
- Evaluate and recommend new data technologies and tools to enhance data capabilities.
- Develop data models that support business intelligence and reporting requirements.
- Document data processes, architectures, and standards.
Requirements
- Bachelor's degree in Computer Science, Engineering, Information Technology, or a related quantitative field.
- Minimum of 5 years of experience in data engineering or a related role.
- Proven experience with big data technologies (e.g., Hadoop, Spark, Kafka).
- Strong proficiency in SQL and programming languages such as Python or Java.
- Experience with cloud platforms (AWS, Azure, GCP) and their data services (e.g., S3, Redshift, Azure Data Factory, BigQuery).
- Hands-on experience with data warehousing concepts and ETL tools.
- Understanding of database design and data modeling principles.
- Experience with data visualization tools (e.g., Tableau, Power BI) is a plus.
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration skills, with the ability to work effectively in a hybrid team environment.
- Familiarity with Agile development methodologies.
Benefits
- Competitive salary and performance bonus.
- Comprehensive medical aid and retirement fund.
- Opportunities for professional development and training.
- Hybrid work model offering flexibility.
- Access to cutting-edge data technologies.
- Challenging projects in the energy sector.
- Generous leave allocation.
- On-site amenities and support.
- Collaborative team environment.
- Career advancement opportunities.