AWS Senior Data Engineer

Goldenrule; South Africa; Vor Ort; ZAR 900.000 - 1.300.000; Vollzeit

Zusammenfassung

Goldenrule is seeking a seasoned Data Engineer to collect, validate, and model business data for insights. You will design robust ETL pipelines and data architectures to enable stakeholders to derive actionable information from large datasets.

With 5–7+ years in an ETL/warehousing environment, you will drive data consolidation, governance, and automation while collaborating across IT operations and business teams in a South Africa context.

Qualifikationen

• 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.

Aufgaben

• Collect and validate business information for data insights.
• Design and implement data models and architectures for insights.
• Develop ETL processes, pipelines, and data validation for accuracy.
• Identify valuable data assets to reduce duplication and improve delivery.
• Develop dashboards, reports, and visualizations of key metrics and trends.
• Help the organization leverage data to drive informed decisions.

Kenntnisse

ETL frameworks

SQL databases

NoSQL

Data virtualization

Cloud certifications

Data warehousing

Ausbildung

Tertiary qualification

Postgraduate qualification

Tools

Databricks

AWS

Azure

Jobbeschreibung

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 an 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.