Intermediate Data Engineer
Johannesburg
Responsibilities:
their wing is currently scouting for a Senior Data Engineer. You will be responsible for developing high fields like Information Systems, Big Data Azure Data Engineer Certification would be advantageous Related
global reach. We are seeking a talented AWS Data Engineer to become a crucial part of their dynamic team
beyond expectations are recruiting for an AWS Data Engineer to join an environment with cutting edge global
institutions worldwide is looking for an Azure Data Engineer. The unique position gives a deep insight into understanding for Data Engineering and Data Warehouse Design Familiar with modern Software engineering concepts Experience: University degree in Computer Science, Data Engineering or a comparable field of study with a focus
FutureSoft is the Leader in the South African Debt Recovery Software Industry. Our software is the Legal and Debt Collection Management System of choice by numerous Law Firms and Debt Collection Agencies across South Africa. We manage and maintain large volumes of data on behalf of our clients. Core
solutions are currently looking for an AWS Data Engineer to join their fast-paced and dynamic team Responsibilities PySpark, Scala, Kafka CC. Design and implement data engineering, ingestion and curation functions on AWS cloud
Hiringnow Currently hiring for Data Engineer for one of the banking clients based in Johannesburg. Min Min of 5-8 years' experience in data engineering • Strong back end and front-end development skills •
based in Sandton is looking for an intermediate Data Engineer in the Risk Technology division. NB: This is Experience, skill and capability: 4-6 years' of Data Engineering experience Excellent data analysis and exploration backup and recovery, data encryption, capacity planning, understanding of database engine internals and all KPIs, dashboards, selfservice BI Azure Cloud Data Engineer Competencies (ideal): Experience in Azure, in deployment pipelines Deliver to all stages of the data engineering process Data ingestion, transformation, data
across the business to align stakeholders with data engineering objectives.