Data Engineer | On-site | George, Western Cape

Badger Holdings is a specialised insurance and related services company. Founded in 1995, we currently employ over 700 staff members across South Africa and Australia and insure over 180 000 clients with premiums in excess of US$100 million. Through a unique blend of skills and expertise, Badger Holdings has grown into a formidable force in the insurance landscape. We have been helping insurance and related companies to maximise their potential for almost two decades. Our success lies in establishing innovative insurance entities and partnering with great people who have excellent track records. We give them the means to grow sustainably into the future by providing expert assistance and advice on legal matters, training needs, marketing requirements and new product development. We believe that it is through partnership that companies will reach their full potential and achieve successful growth. That is why Badger Holdings embraces and encourages opportunities to establish firm, committed and longstanding business relationships. Our chairman often tells the story that inspired his vision for the group – about his friend who was about to crash in a glider plane. He prayed to be saved and felt a gentle wind lift the wings of the plane and gently help to land him. We see relationships and gentle landings in times of need as our offering.What you'll be doing (and why it matters) You'll play a key role in building the foundation that powers data across the business. Working closely with analysts, data scientists, and stakeholders, you'll design and deliver data solutions that turn raw data into something trusted, usable, and impactful. A big part of your focus will be helping us move from legacy systems to a modern stack using Estuary, dbt, GCP, and Snowflake, not just executing the migration, but helping define how we do things going forward. Requirements Your day-to-day will include: Designing and building scalable ELT pipelines from multiple data sources Developing clean, well-structured data models using dbt Optimising data models and workloads within Snowflake Transforming raw data into high-quality, analytics-ready datasets Implementing data quality checks, monitoring, and observability Improving performance and managing cloud cost efficiency Applying engineering best practices (CI/CD, testing, code reviews) Collaborating with cross-functional teams to deliver practical, scalable solutions Contributing to standards, documentation, and mentoring junior engineers What you bring You're someone who takes ownership, enjoys solving problems, and cares about doing things properly, not just quickly. Requirements: 4 - 6+ years' experience in Data Engineering or a similar role Strong SQL skills and experience working with complex transformations Proficiency in Python (or similar) for data processing and automation Experience building ELT pipelines in cloud environments (AWS, Azure, or GCP) Hands-on experience with modern data warehouses (e.g. Snowflake, Synapse) Familiarity with tools like dbt, Airflow, or Dagster Experience working with structured and semi-structured data (JSON, Parquet) A solid understanding of data governance, security, and best practices Bonus if you've worked with: Real-time/streaming technologies (Kafka, Spark Streaming) BI tools like Qlik, Power BI, Looker, or Tableau Qlik Replicate / Compose or similar tools Agile delivery environments (Jira, Azure DevOps) Cloud certifications or exposure to DevOps practices Why this role is worth your time You'll help build (not inherit) a modern data platform You'll work with a forward-looking tech stack (dbt, Snowflake, GCP) You'll have real input into architecture, standards, and best practices You'll be part of a growing data function where your impact is visible You'll have the opportunity to mentor and shape how the team evolves