Senior Data Engineer (Hybrid)
Senior Data Engineer for a data analytics firm in Nelspruit, South Africa, working hybrid from their office. Day to day: designing and maintaining scalable ETL/ELT pipelines, cloud data warehouses and data models using SQL, Python and platforms like Snowflake/AWS, plus mentoring junior engineers.
- Compensation
- Not disclosed
- Location
- Mpumalanga, South Africa
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Bachelor's degree in Computer Science, Engineering, or related quantitative field
- 5+ years of experience in data engineering or related role
- Strong proficiency in SQL and experience with relational database management systems
- Experience with cloud data platforms (AWS, Azure, GCP) and their data services
- Proficiency in at least one programming language such as Python, Scala, or Java
- Hands-on experience with ETL/ELT tools and data warehousing concepts
- Familiarity with big data technologies (e.g., Spark, Hadoop)
- Experience with data modeling techniques
- Understanding of data governance and data quality principles
- Excellent problem-solving and analytical skills
- Strong communication and collaboration skills for a hybrid team
Full description
About the Role
Our client, a rapidly growing data analytics firm based in Nelspruit, is seeking an experienced Senior Data Engineer to join their innovative team. This hybrid role offers the flexibility to work both remotely and from our modern Nelspruit office. You will be responsible for designing, building, and maintaining scalable and reliable data pipelines and infrastructure that power our data science and business intelligence initiatives. This is a crucial role where you will work with large, complex datasets, implementing best practices in data warehousing, ETL/ELT processes, and data modeling. We are looking for a proactive individual who can contribute to architectural decisions and mentor junior engineers, driving efficiency and data quality across the organization. Your work will directly impact our ability to derive insights and make data-driven decisions.
Key Responsibilities
- Design, develop, and maintain robust, scalable, and efficient ETL/ELT pipelines.
- Build and manage data warehouses and data lakes using modern cloud-based technologies (e.g., Snowflake, Redshift, BigQuery).
- Develop and optimize data models for analytical and reporting purposes.
- Implement data quality checks and monitoring to ensure data accuracy and consistency.
- Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.
- Automate data processes and improve the reliability and performance of data infrastructure.
- Work with big data technologies such as Spark, Hadoop, or similar frameworks.
- Ensure data security and compliance with relevant regulations.
- Optimize database performance and query efficiency.
- Mentor junior data engineers and contribute to best practices within the team.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related quantitative field.
- 5+ years of experience in data engineering or a related role.
- Strong proficiency in SQL and experience with relational database management systems.
- Experience with cloud data platforms (e.g., AWS, Azure, GCP) and their data services.
- Proficiency in at least one programming language such as Python, Scala, or Java.
- Hands-on experience with ETL/ELT tools and data warehousing concepts.
- Familiarity with big data technologies (e.g., Spark, Hadoop).
- Experience with data modeling techniques.
- Understanding of data governance and data quality principles.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills, essential for a hybrid team.
Benefits
- Competitive salary and performance bonus.