Senior Data Engineer - Snowflake at NetStone Global Ltd, London, 6 Months, £Contract Rate

Senior Data Engineer - Snowflake

Experience: 10+ Years
Job Type: Contract

Job Overview

We are seeking an experienced Senior Data Engineer - Snowflake with a strong background in designing, developing and optimising scalable data engineering solutions. The ideal candidate will have extensive experience in Snowflake, SQL, Python, ETL/ELT pipelines and cloud-based data platforms.

Key Responsibilities

• Design, develop and maintain scalable data pipelines and data warehouse solutions using Snowflake.
• Build and optimise ETL/ELT processes to support business intelligence, analytics and reporting.
• Develop data models, data marts and reusable data products for downstream applications.
• Integrate Snowflake with cloud platforms, APIs and enterprise data sources.
• Implement performance tuning, query optimisation and data quality improvements.
• Ensure data governance, security and compliance with enterprise standards.
• Collaborate with architects, analysts and business stakeholders to deliver data solutions.
• Work within Agile teams to deliver high-quality data engineering projects.

Required Skills & Experience

• 10+ years of overall IT experience.
• 5+ years of hands-on Data Engineering experience.
• 3+ years of strong Snowflake development and implementation experience.
• Advanced SQL and Python programming skills.
• Strong experience in data warehousing, data modelling and ETL/ELT development.
• Experience with AWS, Azure or GCP cloud environments.
• Knowledge of Snowflake performance optimisation, integration and security.
• Experience delivering data products through APIs, data marts and reporting platforms.
• Strong understanding of data governance, data quality and modern data architectures.
• Excellent communication, stakeholder management and problem-solving skills.
• Experience working in Agile delivery environments.

Desirable Skills

• Snowflake certification.
• Experience with dbt, Airflow or similar data orchestration tools.
• CI/CD pipelines and DevOps practices for data engineering.
• Experience with Real Time data processing and cloud-native services.