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    • Data Engineer - Johannesburg - NedBank

    NedBank
    NedBank Johannesburg

    1 month ago

    Nedbank background
    Description
    Job Classification

    138098 - Data Engineer

    Job Family

    Information Technology

    Career Stream

    Data

    Leadership Pipeline

    Manager of Self Professional

    Job Purpose

    The purpose of the Data Engineer is to leverage their data expertise and data related technologies, in line with the Nedbank 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 bank 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 Bank's strategy to become a data driven organisation.

    Job Responsibilities
    • Loan IQ is by definition a complex lending solution, and the data aspect is critical to not only the involved lenders/borrowers, but also the direct business-users and a multitude of downstream users of the data, ranging from operational staff, finance, balance-sheet management, funding and regulatory areas.
    • A deep understanding of the data-construct is essential as well as insight on the interpretation thereof. Furthermore, the business and domain squad aspire to develop and mature digital offerings, straight-through processing capabilities and optimise for processes.
    • An ability to make data an asset in these ventures will be critical.
    • Responsible for the maintenance, improvement, cleaning, and manipulation of data in the bank's operational and analytics databases.
    • Data Infrastructure: Build and manage scalable, optimised, supported, tested, secure, and reliable data infrastructure eg using Infrastructure and Databases (DB2, PostgreSQL, MSSQL, HBase, NoSQL, etc), Data Lakes Storage (Azure Data Lake Gen 2), Cloud-based solutions (SAS, Azure Databricks, Azure Data Factory, HDInsight). Ensure data security and privacy in collaboration with Information Security, CISO and Data Governance.
    • Data Pipeline Build (Ingestion, Provisioning, Streaming and API): Build and maintain data pipelines to:
    • create data pipelines for data integration (Data Ingestion, Data Provisioning and Data Streaming) utilising both On Premise tool sets and Cloud Data Engineering tool sets.
    • efficiently extract data (Data Acquisition) from Golden Sources, Trusted sources and Writebacks with data integration from multiple sources, formats and structures.
    • load the Nedbank Data Warehouse (Data Reservoir, Atomic Data Warehouse, Enterprise Data Mart).
    • provide data to the respective Lines of Business Marts, Regulatory Marts and Compliance Marts through self-service data virtualisation.
    • provide data to applications or Nedbank Data consumers.
    • transform data to a common data model for reporting and data analysis, and to provide data in a consistent, usable format to Nedbank data stakeholders.
    • Data Modelling and Schema Build: In collaboration with Data Modellers, create data models and database schemas on the Data Reservoir, Data Lake, Atomic Data Warehouse and Enterprise Data Marts.
    • Nedbank Data Warehouse Automation: Automate, monitor and improve the performance of data pipelines.
    • Collaboration: Collaborate with Data Analysts, Software Engineers, Data Modelers, Data Scientists, Scrum Masters and Data Warehouse teams as part of a squad to contribute to the data architecture detail designs and take ownership of Epics end-to-end and ensure that data solutions deliver business value.
    Technical Knowledge
    • Advanced SQL
    • Advanced Data Analysis
    • Database skills and understanding of DB tables relationships
    • Data Modelling
    • Advanced Excel (including advanced functions, pivot tables etc)
    • Data Governance principles
    • Understanding of ETL Processes
    Essential Qualifications - NQF Level
    • Matric / Grade 12 / National Senior Certificate
    • Advanced Diplomas/National 1st Degrees
    Preferred Qualification

    NQF Level 6 Qualification in Computer Science or Information Technology

    Preferred Certifications

    Cloud (Azure, AWS), DEVOPS or Data engineering certification. Any Data Science certification will be an added advantage, Coursera, Udemy, SAS Data Scientist certification, Microsoft Data Scientist.

    Minimum Experience Level
    • 7 to 10 years practical development experience
    Technical / Professional Knowledge
    • Cloud Data Engineering (Azure, AWS, Google)
    • Data Warehousing
    • Databases (PostgreSQL, MS SQL, IBM DB2, HBase, MongoDB)
    • Programming (Python, Java, SQL)
    • Data Analysis and Data Modelling
    • Data Pipelines and ETL tools (Ab Initio, ADB, ADF, SAS ETL)
    • Agile Delivery
    • Problem solving skills
    Behavioural Competencies
    • Decision Making
    • Influencing
    • Communication
    • Innovation
    • Technical/Professional Knowledge and Skills
    • Building Partnerships
    • Continuous Learning
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