Lead Data Engineer

at  iOCO

TECHNICAL SKILLS:

• Proficiency in Azure data services (Azure Data Factory, Azure SQL Database, Azure Data Lake, etc.).
• Strong experience with SSIS for ETL processes.
• Advanced skills in SSRS and SSAS for reporting and analytics.
• Expertise in Power BI for data visualization and dashboard creation.
• Experience with SQL and database management.
• Knowledge of data warehousing concepts and best practices.
• Soft Skills: Strong problem-solving abilities, excellent communication skills, and a proven track record of leading and mentoring teams.

THE ROLE

We are seeking a highly skilled and experienced Lead Data Engineer to join our dynamic team in Cape Town. The ideal candidate will play a critical role in designing, developing, and optimizing our data infrastructure, ensuring it meets the needs of our growing business. As a Lead Data Engineer, you will lead a team of data professionals, drive data initiatives, and ensure the seamless integration of data across the organization.

WHAT YOU’LL DO:

• Lead Data Strategy: Develop and implement data engineering strategies that align with business objectives and support data-driven decision-making.
• Design and Architecture: Design and architect scalable and efficient data solutions on the Azure platform, ensuring high availability and performance.
• ETL Processes: Lead the development and optimization of ETL processes using SSIS to ensure timely and accurate data flow across systems.
• Data Warehousing: Manage and maintain the data warehouse environment, including the design and deployment of SSAS cubes to support analytics and reporting needs.
• Reporting and Analytics: Oversee the creation and maintenance of complex reports and dashboards using SSRS and Power BI, providing actionable insights to stakeholders.
• Data Governance: Implement and enforce data governance policies to ensure data quality, security, and compliance with industry standards.
• Team Leadership: Mentor and lead a team of data engineers, providing technical guidance, fostering professional development, and ensuring the delivery of high-quality work.
• Collaboration: Work closely with cross-functional teams, including Data Analysts, Business Intelligence professionals, and IT teams, to support their data needs and drive data initiatives.
• Continuous Improvement: Identify opportunities to improve data processes, tools, and technologies, and lead initiatives to implement these improvements.