Data Engineer

at  DataTech Recruitment

Are you a passionate and experienced Data Engineer looking for an exciting opportunity in Johannesburg? We are seeking a highly skilled individual with a BSc Degree in Computer Science, Engineering, Mathematics, Statistics, Information Systems, or a related discipline, along with a minimum of 5 years’ experience in building data pipelines including at least 3 years developing multidimensional and tabular models with large and complex datasets. You should be Microsoft certified as an Azure Data Engineer/Azure Solutions Architect Associate or hold equivalent cloud certifications, and possess advanced knowledge in SSIS, SQL, SSAS Cubes, DAX, MDX, Power BI, and Oracle databases.
If you are a dynamic professional who thrives on collaboration, innovation, and is eager to contribute to the evolution of cutting-edge data solutions, we want to hear from you!
Type: Permanent
Salary: R500 000 – R800 000 CTC Per Annum
Area: Johannesburg North - Onsite
Impact you’ll make:
As a Data Engineer, you’ll play a pivotal role in driving data-driven decision-making and innovation within the organization. Your expertise in building robust data pipelines, modelling complex datasets, and developing enterprise data warehouse solutions will empower the teams to unlock valuable insights and make informed choices. You’ll collaborate closely with data scientists, business stakeholders, and cross-functional teams, ensuring the data infrastructure aligns with the strategic vision and supports future growth. Your contributions will directly impact the ability to streamline processes, optimize performance, and deliver exceptional products and services to the customers.

What You’ll Do:

• Data Wrangling: Collaborate with data scientists to prepare and transform data sets for analytical modelling.
• Strategic Alignment: Contribute to and ensure solutions align with the company’s technology evolution roadmap.
• Data Governance: Ensure adherence to data standards, principles, and best practices, while aligning short-term deployments with long-term strategic delivery.
• Risk Assessment: Assess external data management opportunities and threats, developing security, backup, and recovery specifications.
• Project Management: Manage and document installations, database developments, and dashboard amendments.
• Performance Optimization: Define requirements for data warehouse scaling to optimize performance and cost management.
• Database Maintenance: Maintain database performance by identifying and resolving production and application development issues.
• Architectural Compliance: Ensure the delivered data warehouse conforms to standards and architectural decisions, resolving design conflicts.
• Technology Innovation: Conduct investigations and analyses into potential technology innovations, delivering data architectures to support future business growth and process streamlining.
• Requirements Gathering: Collaborate with business process owners and management to determine database structural requirements.
• Data Warehouse Development: Design solutions and update the data warehouse infrastructure to manage organizational data requirements, including daily monitoring and management of database functionality and performance.
• Algorithm Development: Develop algorithms and manage data warehouse processes, visualization, and reporting using ALM tools.
• Reporting: Develop data management reports for business stakeholders to support analyses and decision-making.
• Standards and Compliance: Develop and communicate standards and processes for database management aligned with legislation, gaming regulation requirements, and security protocols.
• Risk Mitigation: Implement control measures and checks to mitigate business risks.
• Continuous Learning: Ensure competence in changing technology and database architecture requirements through training and updates.
• Testing and Auditing: Conduct testing and audit compliance of new or enhanced products to meet stakeholder requirements.
• System Architecture: Ensure a complete understanding of information flow and system architecture in relation to underlying data structures.
• Data Issue Resolution: Review interface tracking dashboards and reports to resolve data issues promptly.
• Regulatory Compliance: Liaise with the Compliance function to discover data regulatory requirements for inclusion in key data policies and standards.
• Stakeholder Coordination: Establish appropriate levels of coordination, communication, and liaison with internal stakeholders to ensure database changes and functionalities remain up-to-date and relevant.

Requirements:

• BSc Degree in Computer Science, Engineering, Mathematics, Statistics, Information Systems, or other technical/quantitative discipline
• Microsoft certified: Azure Data Engineer/Azure Solutions Architect Associate or equivalent cloud certifications
• Certifications in data modeling, data warehousing, project management
• Minimum 5 years of experience building data pipelines, including at least 3 years developing multidimensional and tabular models with large and complex datasets
• High degree of proficiency in SSIS, SQL, SSAS Cubes, DAX, MDX, and building stored procedures
• Advanced knowledge and skills in Oracle databases
• Power BI experience
• Experience with data migration and integration
• Experience building data dictionaries, dimensional data models, architecture diagrams, metadata repositories, data integration processes, ETL processes, and data quality
• Experience with developing enterprise data warehouse solutions, data modelling, and development
• Passion for data and analytics
• Project management skills
• Verbal and written communication skills
• Knowledge of Agile SDLC methodology
• Azure Synapse SQL experience
• Experience in DevOps
• Ability to learn new applications and technologies quickly
• Analysing, creating, and improving skills
• Sourcing information skills
• Applying expertise and technology skills
• Managing relationships skills
• Taking ownership skills
• Responding with urgency skills
• Collaborating skills
• High adaptability
• Business acumen

• Data Wrangling: Collaborate with data scientists to prepare and transform data sets for analytical modelling.
• Strategic Alignment: Contribute to and ensure solutions align with the company’s technology evolution roadmap.
• Data Governance: Ensure adherence to data standards, principles, and best practices, while aligning short-term deployments with long-term strategic delivery.
• Risk Assessment: Assess external data management opportunities and threats, developing security, backup, and recovery specifications.
• Project Management: Manage and document installations, database developments, and dashboard amendments.
• Performance Optimization: Define requirements for data warehouse scaling to optimize performance and cost management.
• Database Maintenance: Maintain database performance by identifying and resolving production and application development issues.
• Architectural Compliance: Ensure the delivered data warehouse conforms to standards and architectural decisions, resolving design conflicts.
• Technology Innovation: Conduct investigations and analyses into potential technology innovations, delivering data architectures to support future business growth and process streamlining.
• Requirements Gathering: Collaborate with business process owners and management to determine database structural requirements.
• Data Warehouse Development: Design solutions and update the data warehouse infrastructure to manage organizational data requirements, including daily monitoring and management of database functionality and performance.
• Algorithm Development: Develop algorithms and manage data warehouse processes, visualization, and reporting using ALM tools.
• Reporting: Develop data management reports for business stakeholders to support analyses and decision-making.
• Standards and Compliance: Develop and communicate standards and processes for database management aligned with legislation, gaming regulation requirements, and security protocols.
• Risk Mitigation: Implement control measures and checks to mitigate business risks.
• Continuous Learning: Ensure competence in changing technology and database architecture requirements through training and updates.
• Testing and Auditing: Conduct testing and audit compliance of new or enhanced products to meet stakeholder requirements.
• System Architecture: Ensure a complete understanding of information flow and system architecture in relation to underlying data structures.
• Data Issue Resolution: Review interface tracking dashboards and reports to resolve data issues promptly.
• Regulatory Compliance: Liaise with the Compliance function to discover data regulatory requirements for inclusion in key data policies and standards.
• Stakeholder Coordination: Establish appropriate levels of coordination, communication, and liaison with internal stakeholders to ensure database changes and functionalities remain up-to-date and relevant