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AWS Senior Data Engineer - Randburg

Purpose of the Position

  • To collect and validate business information (which can then be used by data scientists and business stakeholders).
  • To design and implement data models and architectures that enable business stakeholders to gain insights from large-scale datasets.
  • To design and develop ETL processes, pipelines, and data validation processes to ensure accuracy and consistency of data.
  • To identify valuable data assets, in order to reduce duplication and enable faster delivery of deeper insights to the ST Operational reporting.
  • Identify key drivers and value creators within user journeys.
  • Developing and maintaining dashboards, reports, and visualizations that provide insights into key business metrics and trends.
  • To help the organizations leverage their data to make informed decisions and improve business outcomes.

Qualifications

  • Minimum suitable tertiary qualification or an equivalent.
  • Post graduate qualification would be advantageous.
  • Cloud Technology Certifications in Databricks, AWS, Azure, Data Engineering and other technologies highly advantageous.

Experience

  • A minimum of 5-7 year in ETL Framework driven environment
  • 5-7 years Multiple database experience advantageous
  • MSSQL/SQL
  • MySQL
  • Postgres SQL
  • No-SQL
  • Data Virtualization
  • AWS data
  • At least 5 years working experience.
  • Knowledge of Data Virtualization and Data Warehousing.
  • Ensure solutions adhere to standards and best practices and participate in solution reviews to ensure all solutions fit within standards
  • Operate within project environments and participate in CII continuous improvement efforts
  • Align to the division’s capability in using operational data to drive consolidated, reusable datasets, reducing data silos and duplication.
  • Provide support to ST Executive Team comprised of IT Operations, Development and Program Management data.
  • Identify opportunities to improve business as usual processes using modern technologies and automation.
  • Work with cross-functional teams to identify data requirements, prioritize data initiatives, and drive solutions that enable data-driven decision making.
  • Analyze operational data performance and effectiveness and provide actionable insights for future planning and optimization.
  • Maintain, build and improve data consolidation and automation from operational data to package data for re-use.
  • Design and implement complex enterprise view reports in existing IT Operational Reporting tools.
  • Analyze and organize raw data.
  • Be accountable for solutions, their sustainability and accuracy as well as delivery deadlines.
  • Share knowledge and practical experience with community and team.
  • Implement best practice Data warehousing development based on methodology adopted for solution by Architecture.
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