IM Specialist Data Engineering & Delivery at Sasol

Short Description / Purpose of Job

• Collect, centralise, model and consolidate large amounts of data from multiple sources by applying data extraction as well as transforming and load techniques which allow organisations to derive valuable business insights from their data to improve decision-making and to enable reporting and analysis.
• Collaborate with business and IM to define necessary architecture / design and build data engineering solutions for business enablement.
• Identify, source, and make available key data required for day-to-day operational reporting and analytics in the analytics ecosystem platform.
• Implement an automated data orchestration and quality solution to guarantee reliable and readily available data.
• Create and publish data products to enable strategic business initiatives in the analytics ecosystem platform.

Recruitment Description / Key Accountabilities

• Drive best practices within the organisation in relation to the strategic integration of a decision to support database and the related software programs used to collect, cleanse, transform, and store data from a variety of operational and external sources.
• Train and coach relevant stakeholder to utilise historical, analytical, and business intelligence requirements as well as data acquisition tools and techniques.
• Design and implement the business intelligence portfolio and enterprise data warehouse.
• Devise and drive the principles, processes, and policies pertaining to an enterprise data model to guarantee consistency of decision support activities across the organisation.
• Define and maintain the data warehouse and business intelligence architecture in order to meet the organisations' needs.
• Perform process audit, control, restart, and scheduling.
• Review significant data models and algorithms used for anomaly detection.
• Examine the deployment options, deploy the data models, and test results.
• Maintain and adapt enterprise data schema.
• Analyse the metadata and develop database structures.
• Appraise current data problems and devise significant data solutions using standard development tools.
• Evaluate existing procedures and standards to establish new ones that better meet the business needs.
• Lead various value adding architectural projects to improve the business value of data through data analysis.
• Conduct continuous ETL impact analysis and provide guidance in tuning and optimisation of ETL jobs.
• Secure data conformance and data lineage and provide trainings for relevant stakeholders on data orchestration.
• Support teams that are facing challenges with extracting, transforming, or loading data.
• Recommend to relevant stakeholders data architecture to meet set requirements of relevant projects.
• Explain the different data architecture models, benefits, and shortcomings of different models to relevant stakeholders when and as needed.
• Participate in various IM forums and work collaboratively with others to identify ways to improve data collaboration and interoperability.
• Evaluate and quality assess the architecture models as a basis for recommending the most appropriate model to suit specific project requirements.
• Advocate for the fundamentals of data security and communicate to relevant stakeholders the organisation’s expectations for data security, data privacy, and confidentiality.
• Apply evidence-based SHE practices in alignment with set standards for safe operations.
• Implement Sasol Group's risk philosophy and enterprise risk management framework.
• Build and maintain positive relationships with relevant internal and external stakeholders to enable proper data extraction and utilisation.
• Continuously improve own skills and knowledge. Complete, implement, and track personal development plan to attain personal performance goals.

Formal Education

• 4  year University Bachelor's Degree or higher

Min Experience

• 5+ relevant years

Tools and Technology Skillsets

• Azure Data Engineering - ETL and automation of testing (Azure Data Factory, Theobald SSIS and Logic Apps)
• Data Architecture
• Data Modelling and Design (eg. SAP PowerDesigner)
• Data Warehousing (eg. Synapse SQL)
• Azure Power Platform Engineering (Power BI)
• Integration with PowerApps or K2 or SharePoint Online or SQL
• DevOps
• Agile

Competencies

• Analytics: The systematic computational analysis of data or statistics.
• Collaboration: The action of working with someone to produce something.
• Data Engineering: Demonstrate experience in and knowledge of various data engineering such as Data Modelling and Design, Data Integration and Interoperability (ETL/ELT), Data Warehousing; and Insights, Analysis and Visualisation.
• Data Management: Knowledge of the theory, purpose, architecture and design of the management, administration and relationships of the organisation's data.
• Self-Mastery: Takes accountability for driving own growth through developing self-awareness, reflecting, seeking feedback and self-correcting.
• Tech Savvy: Knowledge of the Information Technology Industry including trends, emerging technology, best practices, competition, regulations, and legislation.
• Verbal Communications: Any exchange of words, either written or spoken, used to transmit information.