Snowflake/DBT Engineer

Contract: Information Technology
Closing date: 23 November 2026
Listed: 19 October 2026, from Plan International

The advert

The Organisation Plan International is an independent development and humanitarian organisation that advances children’s rights and equality for girls. We believe in the power and potential of every child but know this is often suppressed by poverty, violence, exclusion and discrimination. And it is girls who are most affected. Working together with children, young people, supporters and partners, we strive for a just world, tackling the root causes of the challenges girls and vulnerable children face. We support children’s rights from birth until they reach adulthood and we enable children to prepare for and respond to crises and adversity. We drive changes in practice and policy at local, national and global levels using our reach, experience and knowledge. For over 85 years, we have rallied other determined optimists to transform the lives of all children in more than 80 countries. We won’t stop until we are all equal. Role Purpose The Snowflake Data/DBT Engineer is responsible for designing, developing, maintaining and optimising Plan International’s cloud-based data platform and data integration solutions. The role delivers scalable, secure, resilient and high-performing data pipelines and data products that enable trusted reporting, analytics, business intelligence and data-driven decision-making across the organisation. Working within the global Data & Analytics function, the role focuses on building and supporting modern ELT processes using Snowflake, dbt and SQL, integrating data from SAP S/4HANA and other enterprise systems into a governed enterprise data platform. The position holder ensures that data engineering solutions are reliable, performant, well modelled, observable, secure, cost-effective and maintainable. The role contributes to data quality, governance, metadata, lineage and data security requirements and supports the continual evolution of Plan International’s modern cloud data architecture. The position holder collaborates closely with business stakeholders, Data Architects, Reporting & Analytics teams, Enterprise Architecture, IT, source-system owners and implementation partners to develop robust, reusable and maintainable data engineering solutions supporting Plan International’s global operations across more than 80 countries. Accountabilities Snowflake Data Engineering Design, develop and maintain scalable ELT pipelines using Snowflake, dbt and SQL. Build reusable, modular and well-tested dbt models following enterprise engineering standards. Develop high-performance analytical and dimensional data models that support enterprise reporting, analytics and self-service BI. Apply appropriate Snowflake optimisation techniques, including effective data modelling, micro-partition pruning, clustering where appropriate, warehouse sizing, workload management and query optimisation. Design and implement incremental processing, change data capture and historisation strategies appropriate to business and technical requirements. Develop reusable engineering patterns, frameworks, macros and packages to improve development efficiency and consistency. Implement robust error handling, monitoring, alerting and automated recovery processes within data pipelines. Ensure data engineering solutions are scalable, secure, resilient, maintainable and aligned with enterprise architecture standards. Apply appropriate Snowflake capabilities, including dynamic tables, streams, tasks and other platform services where they provide an effective solution to business requirements. Data Integration & ETL Development Develop and support enterprise ETL/ELT solutions integrating SAP S/4HANA and other enterprise source systems into Snowflake. Design and maintain data ingestion and integration processes using SNP Glue and associated technologies. Apply appropriate integration and orchestration patterns, including scheduled, event-driven and API-based processing where required. Develop incremental loading, CDC and automated data validation

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