An International Mining Company has a Contract position available for a Data Engineer.
A technology focused individual, data engineers will need to design, configure, develop and deploy data transformations.
PLEASE NOTE'; THIS IS A CONTRACT POSITION. ONLY APPLY IF YOU QUALIFY IN FULL
Develop ETL pipelines. The data transformations will be developed in Azure Databricks using Python and on Azure SQL using T-SQL and deployed using ARM templates
Combine and curate data in a central data lake
Serve data for application and analytics through a variety of technologies such as SQL, Server Synapse, CosmosDB and TSI
Build transformation pipelines into dimensions and facts and therefore a strong knowledge of standard BI concepts is mandatory
Build stream pipelines leverage IoT Hub, Event Hub, Databricks streaming and other Azure stream technologies.
An undergraduate qualification (Bachelor's degree or equivalent) in the relevant IM discipline and/or Technical competencies and certification with relevant years of experience in a similar role.
Role-specific knowledge:
Data Lake
Data Modeling
Data Architecture
Azure Data Environment
Specialist Areas: Unstructured Data - Applies to /wiki/spaces/DAGDG/pages/1473251810 and any products that handles large scale data such as images. Strong experience of building large scale file shipping and pipelines, ideally using Azure services such as AzCopy and Azure Data Lake. Experience of managing unstructured file meta-data, conversions, standardisation and related workflows. Experience of building analysis jobs that scale on technologies such as Databricks or Azure Batch.
Safety Knowledge: Provides a consistent outstanding role model concerning Safety practices with a deep understanding of the importance of safety
Key Skills:
Phyton – Proficient
PySpark - Proficient
SQL – Competent
Solution Architecture – Competent
API Design - Competent
Containers – Competent
CI/CD – Competent
Azure Cloud - Competent
Data Stream patterns and technology – Proficient
Data stream patterns and technology – Proficient
Data engineering design patterns – Competent
Mining data
Work in a fluid environment with changing requirements whilst maintaining absolute attention to detail.