Senior Data Engineer
Test Triangle · City of London, England, United Kingdom
IT Services and IT Consulting · 51-200 employees
About the role
Design, develop, and optimize enterprise-scale data pipelines and warehouse solutions using Snowflake and AWS. Collaborate with cross-functional teams to translate business requirements into robust technical data engineering workflows.
What they look for
Requirements
Requires 8–15 years of experience in data engineering with strong expertise in Snowflake, Python, PySpark, and Airflow. Candidates should possess deep knowledge of cloud-based data architecture and experience in large-scale data migration initiatives.
Full description
Role Summary
We are seeking a highly skilled Senior Data Engineer with 8–15 years of experience in designing, developing, and implementing enterprise-scale data solutions. The ideal candidate will possess strong expertise in Snowflakeand hands-on experience with Python, PySpark, AWS, and Airflow for building scalable, high-performance data platforms. The role demands strong technical leadership, problem-solving capabilities, and the ability to collaborate effectively with cross-functional teams to deliver robust data engineering solutions.
Key Responsibilities
- Design, develop, and optimize data pipelines and data models using Snowflake for enterprise analytics and reporting
- Write and optimize complex SQL / PL‑SQL queries, procedures, and transformations to support large‑scale data processing
- Build and optimize enterprise data warehouse solutions on Snowflake.
- Develop data ingestion, transformation, and orchestration workflows using Python, PySpark, and Airflow.
- Develop and optimize complex SQL queries, stored procedures, views, streams, and tasks in Snowflake.
- Implement scalable cloud-based data solutions leveraging AWS services.
- Ensure data quality, governance, security, and compliance across the data platform.
- Perform query tuning, performance optimization, and cost optimization within Snowflake.
- Automate deployment and monitoring through CI/CD and DevOps practices.
- Collaborate with business stakeholders, architects, analysts, and engineering teams to translate business requirements into technical solutions.
- Troubleshoot production issues and implement preventive measures to enhance platform reliability.
Preferred Experience
- Experience in large-scale cloud data migration initiatives.
- Strong understanding of enterprise data architecture and modern data platforms.
- Experience working with structured, semi-structured, and unstructured data.
- Exposure to Banking, Financial Services, or other large enterprise environments will be an added advantage.
- Experience in leading technical discussions and mentoring engineering teams.
