Data Engineer

Experience

• Minimum 3-5 years of experience in data engineering, data analytics, or related technical field, with demonstrated experience in designing and implementing data pipelines and analytics solutions

Skills

• Data Platform Technologies: Comprehensive understanding of modern data architecture patterns including Data Lake, Data Warehouse, Data Lakehouse, and Data Mesh concepts. Ability to evaluate and recommend appropriate architectural approaches based on business requirements and technical constraints.
• Technical Programming Skills: Proficient in Python programming language with experience in data manipulation libraries (pandas, numpy), data pipeline frameworks, and API development. Strong SQL skills for data querying, transformation, and database management across various database platforms.
• Data Engineering Practices: Solid foundation in data engineering principles including data ingestion, transformation, quality assurance, and pipeline orchestration. Knowledge of data analysis techniques and data management practices including data governance, lineage tracking, and metadata management.
• Cloud and Platform Experience: Knowledge of Databricks and AWS cloud services will be an advantage, including experience with cloud-based data processing, storage solutions, and managed analytics services. Familiarity with infrastructure-as-a-code and DevOps practices for data platforms
• Problem-Solving and Communication: Strong analytical and problem-solving skills with the ability to troubleshoot complex data issues and optimise system performance. Excellent communication skills to effectively collaborate with both technical and non-technical stakeholders, and ability to translate business requirements into technical solutions.
• Experience with GIS platforms (e.g., ArcGIS), geospatial APIs, routing engines, or 2D/3D mapping technologies a bonus