Data Engineer DBT (Snowflake)

Role Overview

This role seeks candidates who are passionate about data transformation and motivated to support enterprise-scale data modernisation initiatives. You will play a key role in assisting clients in migrating legacy ETL pipelines into dbt on Snowflake by developing scalable transformation models, improving data reliability, and ensuring consistency across analytical platforms. The position contributes directly to enabling modern ETL architecture that supports business intelligence reporting and advanced analytical use cases.

Responsibilities

• Code conversion, refinement and optimization – Convert SSIS transformations into dbt staging/intermediate/mart models, review and validate tool-converted dbt transformations to ensure accuracy, maintainability, and alignment with enterprise modelling standards.
• Data validation and reconciliation - Perform source-to-target validation, row-level and column-level reconciliation, and regression testing to ensure transformation accuracy during migration cycles.
• Incremental pipeline implementation - Implement incremental loading strategies, snapshots, and dependency-aware model execution to support efficient and scalable transformation workflows.
• Documentation and lineage support - Maintain transformation documentation, mapping logic, testing evidence, and lineage metadata to support governance and audit readiness.
• Collaboration & Delivery Support - Work closely with Snowflake engineers, QA teams, and client stakeholders to resolve transformation discrepancies and ensure timely migration delivery.
• ETL/ELT Development & Integration – Build and maintain ETL/ELT workflows using Snowflake-native features or external tools (dbt, Airflow).

Requirements

• 3+ years of experience in dbt, data engineering, or ETL/ELT development.
• Strong SQL development skills and experience in building complex transformation queries.
• Hands-on experience with dbt Core and modular model development.
• Experience converting legacy ETL pipelines (SSIS) into ELT frameworks.
• Experience implementing incremental model and snapshot strategies in dbt.
• Experience with source-to-target reconciliation and transformation validation.
• Understanding of dimensional data modelling (star/snowflake schemas).
• Experience with YAML configuration and Jinja templates.
• Familiarity with version control systems (GIT/Azure DevOps).
• Familiarity with Snowflake SQL execution environment and components (Warehouses, Streams, Tasks, Stages, Time Travel, Data Sharing).
• Bachelor’s or Master’s degree in Computer Science, Information Technology, or equivalent.

Nice to Have

• Exposure to dbt Cloud deployment workflows.
• Experience working with AI-assisted migration tools.
• Experience with Airflow or similar orchestration platforms.
• Knowledge of performance optimization techniques in Snowflake.
• Understanding of CI/CD for data pipelines.

Skills

• dbt
• Snowflake
• SQL
• SSIS
• Airflow