Data Engineer
Our client is one of the world’s leading providers of reinsurance and specialist insurance products. The business provides a comprehensive and broad range of solutions for clients to manage their economic risk and operates through a network of global offices across London, The Americas, EMEA and Asia Pacific regions. We are now looking for a Data Engineer to join their busy and growing team.
Data Engineer - 2-3 year contract inside IR35
London – hybrid
£400-700 per day
To be successful in this role:
You will be a confident and skilled Azure Data Engineer who possesses strong development expertise.
Other requirements for this role include:
Bachelor’s degree in Computer Science, Information Systems, Statistics, or a related field; Master’s level degree is preferred
Microsoft Certified; Azure Data Engineer Associate certification is a plus
Job role and responsibilities:
As a Data Engineer you will be a pivotal member of our clients growing IT team with their Actuary Group and will be responsible for Involvement in several key aspects of designing, building, and maintaining robust data solutions and pipelines on the Microsoft Azure platform. You will collaborate with cross-functional teams to understand business requirements and translate them into scalable data architectures.
Other responsibilities for this role include:
• Subject Matter Expertise:
• Integrate, transform, and consolidate data from various structured, unstructured, and streaming sources
• Create suitable schemas for building analytics solutions
• Data Exploration and Understanding:
• Help stakeholders gain insights into data through exploration
• Build and maintain secure, compliant data processing pipelines
• Utilize different tools and techniques to achieve these goals
• Azure Services and Frameworks:
• Collaborate with various Azure data services and frameworks to store and produce cleansed, enhanced datasets for analysis
• Key services include Azure Data Factory, Azure Synapse Analytics & Azure Data Lake Storage
• Data Architecture Patterns:
• Design data stores with different architecture patterns based on business requirements, such as Modern Data Warehouse (MDW) and Big Data Lakehouse architecture
• Operationalization and Optimization:
• Ensure that data pipelines and data stores are high-performing, efficient, organized, and reliable
• Identify and troubleshoot operational and data quality issues
• Design, implement, monitor, and optimize data platforms to meet data pipeline requirements
• Data Processing Languages:
• Proficiency in data processing languages such as SQL & Python
Benefits:
• The business is an equal opportunity employer with excellent benefits and a strong commitment to providing training and opportunities for staff. The business provides employees with an innovative, enriching environment and takes great pride in their career growth.
