BETSoftware
Junior Data Engineer
BETSoftware, a South African betting/gaming software company, is hiring a Junior Data Engineer in Gauteng to build and support batch data pipelines, monitor data loads, and write SQL/Python scripts under senior guidance. Core stack includes SQL Server, Python, Airflow, Git/Azure DevOps, Spark/PySpark, Kafka/Redpanda, and ClickHouse.
- Compensation
- Not disclosed
- Location
- Gauteng, South Africa
- Work setup
- Not specified
- Seniority
- Junior
- Employment
- Not specified
- Experience
- 1+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Degree, diploma, or relevant certification in IT, Computer Science, Engineering, Information Systems, or related discipline
- Minimum 1+ years experience in data engineering, software development, ETL/ELT, database development, or related role
- Foundational SQL skills: writing queries, joining datasets, basic transformations
- Understanding of relational databases and structured data concepts
- Understanding of data pipelines, ETL/ELT, and batch processing concepts
- Some exposure to Python, data processing, scripting, or automation
- Familiarity with version control systems, particularly Git
- Ability to troubleshoot, debug, and resolve technical issues
- Willingness to learn modern data platform tools, engineering practices, and production support
- Strong analytical, problem-solving, and communication skills
- Ability to collaborate with technical and non-technical stakeholders
- Attention to detail when working with business-critical data
Nice to have
- Data warehousing, dimensional modelling, or analytical data concepts
- Workflow orchestration tools such as Airflow or SQL Server Agent
- Cloud or on-premises object storage concepts
- Distributed processing, streaming, or lakehouse concepts
- Tools such as Spark, PySpark, Kafka, Redpanda, ClickHouse, Iceberg, or Delta Lake
- Exposure to CI/CD, deployment automation, or engineering workflows
- Interest in monitoring, alerting, observability, and operational support for data workloads
- Comfort working with documentation, runbooks, and team standards
Full description
Job Description
- Proficiency in SQL and data querying fundamentals.
- Understanding of relational databases and structured data management.
- Knowledge of data pipelines, ETL/ELT processes, and batch data processing concepts.
- Ability to troubleshoot, debug, and resolve technical issues.
- Familiarity with version control systems, particularly Git.
- Exposure to Python or similar scripting languages for data-related tasks.
- Understanding of data warehousing, dimensional modelling, and analytical data concepts.
- Familiarity with workflow orchestration tools such as Airflow or SQL Server Agent.
- Knowledge of cloud and on-premises storage concepts.
- Awareness of distributed processing, streaming architectures, and lakehouse technologies.
- Exposure to modern data engineering tools and platforms, including Spark, PySpark, Kafka, Redpanda, ClickHouse, Iceberg, and Delta Lake.
- Understanding of monitoring, observability, alerting, and operational support practices for data workloads.
- Familiarity with CI/CD pipelines, deployment automation, and engineering best practices.
- Ability to work effectively with technical documentation, runbooks, and team standards.
- Strong analytical, problem-solving, and communication skills.
- Ability to collaborate with technical and non-technical stakeholders.
- High attention to detail when working with business-critical data.
- Strong accountability, ownership mindset, and commitment to continuous learning and professional growth in data engineering.
Job Responsibilities
Data Pipeline Support & Development
- Help build, maintain, and support batch data pipelines under the guidance of more experienced engineers.
- Assist with ingestion, transformation, and data preparation tasks across the enterprise data platform.
- Write and maintain SQL queries, scripts, and basic processing logic for data workflows.
- Support the improvement of existing pipelines by helping resolve defects, inefficiencies, and data issues.
Data Platform Operations
- Monitor scheduled pipelines and help investigate failures, alerts, and data discrepancies.
- Assist in validating data loads and checking that datasets are complete, accurate, and available when expected.
- Help maintain documentation for data flows, processes, dependencies, and operational procedures.