Snowflake Data Engineering- Remote

FDM is a global business and technology consultancy seeking a Snowflake Data Engineer to work for our client within the Finance sector. This is initially a 12 month contract with very good prospects to extend and will be a remote role.

Our client is seeking an experienced Snowflake Data Engineer to join a high-performing data team to support with the expansion of it's enterprise data platform. This role will focus on the design, development and optimisation of Snowflake-based data solutions that support critical business functions including Underwriting, Claims, Finance, Portfolio Management and Delegated Authority reporting.

The successful candidate will combine strong technical data engineering expertise with a solid understanding of London Market insurance processes and data.

Responsibilities:

Snowflake Data Engineering

• Design, develop and maintain scalable Snowflake data pipelines and ELT processes.
• Build and optimise data models across Raw, Curated and Gold layers.
• Develop reusable engineering frameworks and deployment patterns.
• Support platform performance tuning, scalability and cost optimisation.
• Implement automated data quality, monitoring and reconciliation processes.
• Ensure auditability, historisation and data lineage requirements are met.
• Contribute to CI/CD, DevOps and release management activities.

Data Integration

• Integrate data from core insurance systems and external sources into Snowflake.
• Develop ingestion and transformation processes using Azure Data Factory and Snowflake.
• Support datasets relating to submissions, policies, premiums, claims, bordereaux, delegated authority and finance.
• Assist with migration and reconciliation activities from legacy data warehouse environments.

Data Modelling and Analytics

• Develop enterprise data models aligned to underwriting, claims and finance requirements.
• Create conformed dimensions and reusable business entities.
• Support semantic modelling requirements for Power BI reporting and analytics.
• Apply best-practice dimensional, star schema and Snowflake modelling techniques.