Snowflake Data Engineer
About the role
We are modernising an enterprise data warehouse to a cloud-native analytics platform on AWS and Snowflake. We are looking for a hands-on Snowflake Data Engineer to build and support reliable ingestion and ELT pipelines, dimensional data models, and production-ready data solutions. The role will work closely with senior engineers, architects, QA, cloud/platform teams, and BI users through design, development, testing, deployment, and operational handover.
Key responsibilities
- Design, develop, and maintain data pipelines and data warehouse layers in Snowflake, including RAW, ODS, and DW schemas, tables, and views.
- Implement data ingestion and orchestration using Snowflake features such as Stages, Storage Integrations, Snowpipe, Tasks, Streams, and Stored Procedures, or equivalent approved patterns.
- Develop and maintain dimensional data models, including fact and dimension tables, transformations, aggregates, and lookup structures.
- Write and optimise SQL for data transformation, reconciliation, troubleshooting, and performance improvement.
- Implement data quality checks, validation, reconciliation, logging, and error-handling controls.
- Support rerun, recovery, and replay activities for failed or incomplete data processing.
- Work with AWS services such as S3 and IAM as part of secure cloud data integration.
- Support SIT, UAT, deployment, documentation, and operational handover activities.
- Collaborate with senior engineers and architects, follow agreed engineering standards, and contribute to code reviews and continuous improvement.
Requirements
- 3+ years of experience in data engineering, data warehousing, or database development.
- Hands-on experience with Snowflake, or practical experience with another cloud data warehouse and the ability to ramp up quickly on Snowflake.
- Strong SQL skills, including joins, window functions, data transformations, and query troubleshooting.
- Good understanding of dimensional modelling, including fact and dimension table design.
- Experience developing or supporting ETL/ELT pipelines and production data workflows.
- Basic understanding of data quality, reconciliation, logging, retry, and operational support practices.
- Ability to work effectively in a delivery team, communicate clearly, and take ownership of assigned datasets or pipeline components.
- Hands-on experience with Snowpipe, Tasks, Streams, Stored Procedures, Stages, or Storage Integrations.
- Oracle Data Warehouse or legacy data platform migration experience.
- Experience handling semi-structured data such as XML, JSON, or Snowflake VARIANT.