Senior Data Engineer

Contract position

Minimum Requirements:

• A bachelors degree in computer science, Information Technology, or Equivalent Qualification.
• 5 years of Data Engineering experience.
• Data warehousing concepts is advantageous.
• Ab Initio development experience (on-prem and cloud) is essential.
• Exposure to UNIX and SQL (DB2, MS SQL and Netezza) and Oracle
• Exposure to Azure Cloud
• An agile working approach is essential.
• Should be a self-starter who can work under minimal supervision.
• Able to work independently. 

Responsibilities:

• Interpret requirements provided by the business and develop accurate and sustainable solutions from the planning stage through to the productionised solution.
• Analyse, interpret and display data sets to ensure data-driven solutions that address challenges and business needs within Organisations.
• 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.
• Design and develop data models, ETL processes, and pipelines to support data ingestion, transformation, and analysis.
• Work with cross-functional teams to identify data requirements, prioritize data initiatives, and drive solutions that enable data-driven decision-making.
• Develop and maintain dashboards, reports, and visualizations that provide insights into key business metrics and trends.
• Design and implement data quality and data validation processes to ensure the accuracy and consistency of data.
• Develop and maintain documentation for data models, data lineage, and data flow.
• Design and develop data models, ETL processes, and pipelines to support data ingestion, transformation, and analysis.
• Work with cross-functional teams to identify data requirements, prioritize data initiatives, and drive solutions that enable data-driven decision-making.
• Develop and maintain dashboards, reports, and visualizations that provide insights into key business metrics and trends.
• Design and implement data quality and data validation processes to ensure the accuracy and consistency of data.
• Develop and maintain documentation for data models, data lineage, and data flow.