Head: Data Engineering
ZAR 435K-600K (estimate) Executive-level Full Time
Tasks
- Build batch and streaming data pipelines
- Define data platform patterns standards and architecture
- Design trusted governed data pipelines
- Drive performance engineering and cost optimization
- Ensure cross discipline integration and alignment
- Establish reusable data products and shared datasets
- Implement DataOps observability and lifecycle management
- Introduce new data engineering technologies through pilots
- Lead data engineering teams
- Lead engineering guilds and codify standards
- Mentor and uplift engineering talent
- Recommend data platform architecture to executives
- Set governance security and compliance practices
- Shape enterprise data platform operating model
Perks/Benefits
- N/A
Skills/Tech-stack
ABAC | AWS | Apache Airflow | Apache Hudi | Apache Iceberg | Apache Spark | Argo Workflows | Avro | Azure | Azure Data | Azure Data Factory | Azure Data Lake | Azure Data Lake Storage | Azure Synapse | CI/CD | Change Data Capture | Collibra | DBT | Data Capture | Data Catalog | Data Contracts | Data Engineering | Data Factory | Data Lake Storage | Data Quality | Data Vault | Data Vault 2.0 | Data Warehousing | Data masking | Databricks | Debezium | Delta Lake | Dimensional Modeling | ELT | ETL | Encryption | Exactly once | Exactly-once processing | FinOps | GCP | GRPC | GitOps | IAM | Idempotent Pipelines | Infrastructure as Code | Kafka | Kinesis | Kubernetes | Lineage | Microsoft Purview | Observability | Parquet | Policy-as-Code | Power BI | Python | RBAC | REST | SQL | SRE | Scala | Schema Registry | Schema evolution | Streaming | Terraform | Tokenization | “as-code”
Education
Master of Science | PhD | Postgraduate Degree in Computer Science
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