Data Engineer

SUMMARY:
We are seeking a skilled Data Engineer with strong ETL experience, a programming background, and expertise in Linux environments. The ideal candidate will be responsible for designing, building, and maintaining scalable data
pipelines to support business intelligence and analytics needs.

The role requires to collaborate closely with data scientists, analysts, and software engineers to ensure efficient data integration and transformation processes.

POSITION INFO:
Minimum Qualifications and Work Experience Required:

• Minimum a 3-year degree in Information Technology. Preferable B.Sc. Computer Science,
• Bcom Informatics (Honours), B.Eng with Computer Science
• 3+ years of experience in data engineering, ETL development, or related roles.
• Proficiency in SQL and experience with relational
• databases (PostgreSQL, MySQL, SQL Server, etc.)
• Experience in a financial sector would be beneficial
• Ab Initio certification beneficial

• Any of 'C', 'C++, Java Cobol and other procedural OO Languages.
• UNIX knowledge, in particular scripting. All consultants will use UNIX.
• Knowledge of a major database: Oracle, DB2, Teradata, Sybase, Informix, Hyperion
• Knowledge or awareness of Business MetaData
• Knowledge or awareness of scheduling
• Knowledge or awareness of data quality and data cleansing (e.g. tools such as SAS Dataflux,
• Trillium et al)
• Knowledge or awareness of real-time applications or web services
• Knowledge or awareness of data warehousing

• Develop, implement, and maintain ETL pipelines to ingest, transform, and store data from multiple sources.
• Design and optimize data models for analytics and reporting.
• Work with big data technologies and cloud platforms to ensure scalable and efficient data processing.
• Develop and maintain data integration solutions between various systems and databases.
• Monitor and troubleshoot data pipeline issues, ensuring data integrity and reliability.
• Automate data workflows using scripting and scheduling tools.
• Optimize SQL queries and database performance.
• Ensure compliance with data governance, security, and best practices.
• Collaborate with cross-functional teams to understand data needs and
• develop solutions accordingly.