Data Engineer

As a data engineer you will implement data flows to connect operational systems, data for analytics and Business Intelligence systems, document source to target mappings, re-engineer manual data flows to enable scaling and repeatable use, support the build of data streaming systems, write ETL scripts and code to ensure the ETL process performs optimally, develop Business Intelligence reports that can be reused, and build accessible data for analysis

• Proven, hands-on experience (ideally 3+ years) developing complex data pipelines, data models, and workflows
• Strong proficiency in Python and at least one key programming language commonly used in data engineering (PySpark/SQL strongly preferred, Java/Scala beneficial).
• Solid understanding and practical experience in designing and implementing effective data models (eg, relational, dimensional) suitable for analytical and operational usecases.
• Deep understanding of ETL/ELT principles, patterns, and best practices for building robust data integration solutions.
• Experience working with large, complex datasets and understanding distributed data processing concepts.
• Excellent analytical and critical thinking skills with a proven ability to troubleshoot complex technical issues independently.
• Strong verbal and written communication skills, with the ability to articulate complex technical concepts clearly to both technical and non-technical audiences.
• Proven ability to work effectively within a team environment and write high quality documentation.
• Demonstrable experience or a strong, genuine interest in mentoring junior colleagues, sharing knowledge, and fostering a supportive team culture. Experience with or enthusiasm for pair programming is essential.
• Proficiency with Git for code management and collaboration.
• Demonstrable experience operating at a level consistent with SFIA Level 4, showing autonomy, influence, complexity management, strong business skills, and deep knowledge in data engineering.