Data Engineer: Enterprise Data Platform & Snowflake Expert

DGH Recruitment; Greater London; On-site; GBP 65,000 - 90,000; Full time

Job summary

DGH Recruitment is seeking a Data Engineer to join a leading professional services organisation's Data & Analytics function in Greater London. You will design and maintain an enterprise data platform, delivering high-quality reporting, analytics, and business insights across the organisation.

You will build scalable pipelines, develop dimensional models, and optimise Snowflake environments while using Azure Data Factory for data integration.

Qualifications

• Experience in data engineering, data architecture, and data modelling.
• Hands-on Snowflake administration and performance tuning.
• Experience using Azure Data Factory for data orchestration.
• Understanding of data warehousing and dimensional modelling principles.
• Ability to explain complex data concepts to business stakeholders.

Responsibilities

• Design and maintain enterprise data platform solutions.
• Build scalable, production-grade data pipelines and transformations.
• Develop dimensional data models to support reporting and analytics.
• Manage and optimise Snowflake environments for performance and cost.
• Create and maintain data ingestion pipelines using ADF.
• Implement data governance, security controls, and access management.
• Contribute to data engineering standards, CI/CD processes.
• Collaborate with stakeholders to deliver data solutions.

Skills

Data engineering

Data architecture

Data modelling

Data governance

Stakeholder communication

CI/CD processes

Tools

Snowflake

Azure Data Factory

Job description

DGH Recruitment is seeking a Data Engineer to join a leading professional services organisation's Data & Analytics function in Greater London. You will design and maintain an enterprise data platform, delivering high-quality reporting, analytics, and business insights across the organisation.

You will build scalable pipelines, develop dimensional models, and optimise Snowflake environments while using Azure Data Factory for data integration.