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 years 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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