Job Description

A Leader in the Financial and Banking sector is on the look-out for a Junior Data Engineer.The purpose of the Data Engineer is to leverage their data expertise and data related technologies, in line with the Company's Data Architecture Roadmap, to advance technical thought leadership for the Enterprise, deliver fit for purpose data produ...POSITION INFO:A Leader in the Financial and sector is on the look-out for a Junior Data Engineer.The purpose of the Data Engineer is to leverage their data expertise and data related technologies, in line with the Company's Data Architecture Roadmap, to advance technical thought leadership for the Enterprise, deliver fit for purpose data products, and support data initiatives. In addition, Data Engineers enhance the data infrastructure of the company to enable advanced analytics, machine learning and artificial intelligence by providing clean, usable data to stakeholders. They also create data pipelines, Ingestion, provisioning, streaming, self service, API and solutions around big data that support the Company's strategy to become a data driven organisation.Required Qualification

• Matric / Grade 12 / National Senior Certificate
• Advanced Diplomas/National 1st Degrees

Preferred Qualification

• Field of Study:Bcom, BSc, BEng

Preferred Certifications

• Cloud (Azure, AWS), DEVOPS or Data

certification. Any Data Science certification will be an added advantage, Coursera, Udemy, SAS Data Scientist certification, Microsoft Data Scientist.Minimum Experience Level

• Total number of years of experience:1 - 2 years
• Type of experience: Result-driven, analytical creative thinker with demonstrated innovative problem solving skills. Self-motivated, proactive and organised with the demonstrated ability to handle-multiple and simultaneous tasks meeting aggressive deadlines. Team player with demonstrated ability to stay calm and composed in the face of adversity. xc3x82 xc3x82

Technical / Professional Knowledge

• Cloud Data Engineering (Azure , AWS, Google)
• Data Warehousing
• Databases (PostgreSQL, MS SQL, IBM DB2)
• Data Analysis and Data Modelling
• Data Pipelines and ETL tools (Ab Initio, ADB, ADF, SAS ETL)
• Agile Delivery

Behavioural Competencies

• Technical/Professional Knowledge and Skills
• Innovation
• Continuous Learning
• Communication
• Collaborating
• Quality Orientation

Key Performance Areas:

• Responsible for the day to day maintenance of data pipelines, providing support to the data squads including performing data related tasks (such as data profiling, data cleaning, data configurations, data support, data validation, data quality assurance) in a Data Epic and assisting in basic data pipelines, data ingestion and supporting Data Engineers in their Epics.xc3x82
• Data Infrastructure: Support and maintain the Data Infrastructure to ensure it is secure, available and reliable.
• Data Pipeline Build (Ingestion, Provisioning, Streaming and API): Maintain data pipelines starting with Data Virtualisation, then progressing to Data Ingestion and finally to Data Provisioning. Ensure that data pipelines are monitored and run successfully and configure and support minor changes in data pipelines.
• Data Visualisation: Create virtual data bases and assist in creating data extracts for the business in response to business needs.
• Documentation and Data Analysis: Collaborate with the Data Analyst to perform data profiling, data validation, and data documentation in support of Epics.xc3x82
• Company's Data Warehouse Monitoring and Support: Monitor data pipelines and infrastructure to provide first line support, resolve issues and ensure that the warehouse meets its SLA timelines for data availability and warehouse reliability.
• Company's Cloud Monitoring and Support Services: Ensure cloud processes (Compute and Storage) are monitored and managed daily, to ensure that Cloud pipelines run successfully.
• Operations: Support and run daily operational reports to ensure that all jobs ran successfully and that the data warehouse is maintained according to standard.
• Collaboration: Work collaboratively with business stakeholders to gain business knowledge, understand data extracts and improve and optimise business queries

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