Senior Data Engineer - Databricks

If you are a Senior Data Engineer who thrives on building modern infrastructure rather than patching up legacy systems, this role gives you the platform to do exactly that. Working in a fully remote capacity for a Sandton-based team, you will drive the design and development of scalable, cloud-driven data solutions.

• Modern Stack Autonomy: You will work in an environment that actively avoids legacy tech, focusing instead on modern tooling to build high-performance data architectures.
• Technical Leadership: This role positions you at the forefront of project delivery. You will lead technical teams, mentor growing talent, and shape engineering best practices within an Agile framework.
• High-Value Impact: A 100% bill-ability model means your time is invested directly into high-visibility client deliverables, avoiding administrative bloat.
• Global Project Variety: You will collaborate on diverse projects for both local and international clients, navigating complex SaaS and PaaS ecosystems.
• Peer-to-Peer Excellence: You will operate alongside a practice that priorities collaborative technical design and code quality.

To succeed here, you should bring more than five years of progressive data engineering and cloud computing experience. You will need to demonstrate deep technical capability across the following areas:

• Cloud & Orchestration: Advanced expertise with Azure, Databricks, PySpark, and Apache Airflow.
• Architecture: Practical experience architecting Data Lakehouses and warehouses using Delta, Parquet, and Avro.
• Development: Strong proficiency in Python and SQL (specifically PostgreSQL or SQL Server), alongside API/Microservices integration and Git version control.
• Methodology: A firm understanding of data modeling nuances, including Kimball versus Inmon, normalization, and NoSQL applications.
• Delivery: Experience managing multi-shore projects and guiding teams through complex technical challenges.

If this sounds like your next role, let's speak!