Data Engineer

Robusta Technology Group (RTG) is a key driver of digital transformation by providing a holistic tech ecosystem. RTG works with its local and international partners to help build digital customer experiences, establish remote engineering hubs and build ventures across multiple industries and domains. In this pursuit, RTG serves as a catalyst for impact and growth through events, spaces and content focused on creating impact and growth across the different interactions. 

Robusta is a tech agency working with a diverse client base across different sectors & industries on implementing digital transformation programs. Engagements are typically focused on digitization of existing operations & processes and/or activation of digital customer engagement channels. With a team of 100+ tech and market consultants, robusta maintains an impactful footprint across EMEA and engages with its clients through its two key operations hubs in Egypt and Germany. 

Key Responsibilities

• Design, develop, and maintain robust ETL processes to extract, transform, and load data into data warehouses and analytical platforms.
• Collaborate with cross-functional teams to gather data requirements and translate business needs into technical solutions.
• Optimize and troubleshoot ETL workflows to ensure performance, reliability, and scalability.
• Implement data quality checks, validation rules, and monitoring procedures.
• Support integration of new data sources and participate in data migration initiatives.
• Work with IT and infrastructure teams to ensure secure, compliant data handling.
• Stay updated on emerging technologies and recommend enhancements to data engineering practices.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, or related field.
• 1–3 years of hands-on experience in ETL development or data engineering.
• Strong SQL skills and experience with relational databases (SQL Server, Oracle, MySQL, etc.).
• Familiarity with cloud platforms (AWS, Azure, or GCP).
• Knowledge of data modelling, warehousing concepts, and data integration techniques.
• Experience with scripting languages (Python, Shell, etc.).
• Ability to analyze complex data sets and troubleshoot pipelines.
• Understanding of data quality, governance, and data management best practices.