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Senior Data Engineer at BET Software Careers Site

Roodepoort, Gauteng, South Africa -

Full Time

Start Date

Immediate

Expiry Date

12 Oct, 26

Salary

0.0

Posted On

14 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Warehousing, Spark, Flink, SQL, Kafka, Iceberg, ClickHouse, Kubernetes, Airflow, ETL/ELT, Data Modeling, CI/CD

Industry

IT Services and IT Consulting

Description

* Data Warehouse, Lake and Lakehouse architecture patterns. * Distributed data processing using frameworks such as Spark or Flink. * Designing and supporting batch and near-real-time ingestion pipelines. * Building incremental, idempotent, and fault-tolerant data pipelines. * Data quality, reconciliation, and observability practices. * Metadata, lineage, governance, and access control concepts. * Analytical data modelling and efficient data structures for warehouse and large-scale query workloads. * Medallion architecture such as Bronze, Silver, and Gold layers. * Open table formats such as Iceberg. * Schema evolution, partitioning strategies, file optimisation, and storage layout tuning. * Event-driven or streaming platforms such as Kafka, Pulsar, or Redpanda. * Columnar or high-performance analytical platforms such as ClickHouse. * CI/CD pipelines, deployment automation, and engineering standards for data workloads. * Experience improving reliability, performance, and scalability across production data platforms. * Familiarity with monitoring, alerting, observability, and operational support practices. * Exposure to containerised or clustered environments such as Kubernetes, OpenShift, or similar platforms. * Strong debugging capability across data, pipeline, compute, and platform layers. * Strong sense of ownership and accountability. * Comfortable making technical trade-offs while remaining pragmatic and hands-on. * Excellent problem-solving and communication skills. * Able to collaborate effectively with technical and non-technical stakeholders. * Passionate about building scalable, maintainable, and well-documented systems. * Committed to sharing knowledge and raising engineering standards across the team.

Responsibilities

Design, build, and improve an enterprise data platform focusing on scalable data pipelines and architectural direction. Ensure the reliability, performance, and observability of production data workloads across the business.