Snowflake/DBT Engineer

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.

Responsibilities

• 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
• 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 processes
• Investigate and resolve data integration issues across multiple platforms, source systems and environments
• Ensure data quality, completeness, consistency and integrity throughout the data lifecycle
• Investigate and reconcile data between SAP S/4HANA and Snowflake to identify discrepancies, data-quality issues and integration defects
• Collaborate with source-system owners to understand data structures, business processes, source-system changes and integration requirements
• Assess the impact of upstream system changes on downstream data pipelines and analytical datasets
• Maintain appropriate technical documentation for source-to-target mappings, integration processes and transformation logic
• Design and implement scalable dimensional and analytical data models aligned with enterprise data architecture principles
• Apply appropriate approaches to data grain, keys, historisation, slowly changing dimensions and reusable/conformed business entities
• Develop trusted, reusable datasets to support Power BI, Microsoft Fabric and other analytical and reporting platforms
• Work with Reporting & Analytics teams to ensure datasets are performant, appropriately structured and fit for analytical consumption
• Ensure transformation logic is transparent, documented and traceable from source through to consumption
• Support the development of reusable semantic and business data structures where required
• Ensure data models support both current reporting requirements and future analytical use cases
• Support DevOps practices including CI/CD pipelines, automated deployments and source-code management
• Maintain version-controlled dbt projects and deployment processes across development, test and production environments
• Implement automated validation and testing as part of the development and deployment lifecycle
• Apply appropriate unit, integration, data-quality and regression testing practices
• Participate in release planning, deployment activities and production support
• Contribute to Infrastructure as Code and automated provisioning practices where applicable
• Monitor platform health, investigate incidents and implement continuous improvements to operational performance
• Develop and maintain technical documentation for engineering solutions, deployment processes and operational procedures
• Establish and maintain appropriate development, testing and production controls
• Work closely with Data Architects and business stakeholders to translate business requirements into scalable technical solutions
• Collaborate with source-system owners to understand business processes, data structures and integration dependencies
• Support Reporting & Analytics teams by delivering trusted, well-modelled datasets for Power BI, Microsoft Fabric and other analytical platforms
• Participate in solution design, technical estimation, planning, testing and implementation activities
• Provide technical input into architecture and design decisions
• Communicate technical risks, dependencies and recommendations clearly to technical and non-technical stakeholders
• Support User Acceptance Testing and production releases where required
• Work effectively with geographically distributed teams across Plan International’s global operating environment
• Collaborate with external implementation partners and technology vendors while maintaining appropriate internal technical knowledge and ownership
• Develop and maintain Snowflake databases, schemas, warehouses and supporting platform configurations in accordance with enterprise standards
• Monitor Snowflake workloads, resource utilisation, performance and platform health
• Optimise Snowflake compute and storage consumption through appropriate warehouse sizing, workload management, query optimisation and data lifecycle practices
• Identify opportunities to improve platform efficiency and reduce unnecessary cloud data costs
• Implement and maintain role-based access controls and least-privilege principles
• Support appropriate implementation of data masking, access policies and other Snowflake security capabilities
• Ensure Snowflake environments are appropriately configured across development, test and production
• Contribute to platform capacity planning and performance management
• Support the implementation of platform resilience, disaster recovery and business continuity requirements
• Work with Enterprise Architecture, IT and technology vendors to ensure the Snowflake platform evolves in line with Plan International’s strategic technology direction
• Monitor critical data pipelines, Snowflake workloads and associated integration processes
• Provide Level 2/3 technical support for data engineering services and production data pipelines
• Investigate incidents, perform root-cause analysis and implement effective remediation
• Ensure recurring production issues are addressed through preventative engineering improvements
• Support agreed availability, reliability and data-freshness SLAs/SLOs for critical data services
• Participate in incident, problem and change management processes
• Contribute to disaster recovery, backup/recovery and business continuity activities
• Ensure operational procedures, runbooks and support documentation are maintained
• Participate in out-of-hours support arrangements where required by the business
• Identify opportunities to improve platform performance, reliability, automation and engineering efficiency
• Promote reusable development patterns, automation and engineering best practice
• Identify opportunities to simplify and standardise data engineering processes and solutions
• Evaluate emerging Snowflake, dbt, cloud and data engineering technologies and recommend improvements where appropriate
• Contribute to the continual evolution of Plan International’s modern cloud data architecture
• Share knowledge and mentor other members of the Data & Analytics function where appropriate
• Promote engineering quality, automation, documentation, testing and operational excellence
• Contribute to the development and continual improvement of enterprise data engineering standards

Requirements

• Work experience in Computer Science, Information Systems, Software Engineering or a related discipline, or equivalent practical experience
• Strong hands-on experience developing solutions using Snowflake
• Strong hands-on experience using dbt for data transformation and modelling
• Advanced SQL development and performance optimisation skills
• Demonstrable experience developing enterprise ETL/ELT solutions
• Practical experience using SNP Glue for enterprise data integration
• Experience integrating data from SAP S/4HANA source systems
• Ability to use SAP Data Browser, including SE16
• Micro Partition Optimization via dbt incremental models and Snowflake dynamic tables for change processing
• Cross-system orchestration using SNP event triggers and dbt API runs
• Macro-enabled dbt package development for semantic modelling and mapping
• Experience designing dimensional and analytical data models
• Experience implementing CI/CD and DevOps practices within modern data engineering environments
• Knowledge of data quality, testing and validation techniques
• Experience working with Git-based source control and collaborative development practices
• Strong analytical and problem-solving skills
• Excellent written and verbal communication skills
• Ability to work independently while collaborating effectively with global teams
• Strong attention to detail and commitment to engineering best practice
• Snowflake certification (desirable)
• dbt certification (desirable)
• Experience with Microsoft Fabric and Power BI (desirable)
• Experience working within Azure cloud environments (desirable)
• Experience working in international development, NGO or humanitarian organisations (desirable)
• Experience with Agile delivery methodologies (desirable)
• Knowledge of data governance and metadata management practices (desirable)
• Experience supporting enterprise-scale cloud data platforms (desirable)

Skills

• Snowflake Development
• dbt Data Transformation
• SQL Development},{
• SQL Performance Optimisation
• ETL/ELT Solution Development
• SNP Glue Integration
• SAP integration
• SAP Data Browser Usage
• Micro Partition Optimization
• dbt Incremental Models
• Snowflake Dynamic Tables
• Cross-System Orchestration
• SNP Event Triggers
• dbt API Runs
• Macro-Enabled dbt Package Development
• Dimensional Modeling
• Analytical Data Modeling
• CI/CD
• DevOps Practices
• Data Quality Testing
• Data Validation Techniques
• Git Source Control
• Collaborative Development Practices

Languages

English