Develop and maintain dbt transformation pipelines under the direction of a senior technical lead.
Write and optimize SQL used for transformation logic, data preparation, and warehouse-based development work.
Work in Snowflake to query, transform, and manage data in support of production delivery.
Build and maintain dbt models, including staging and transformation layers.
Support data quality and validation activities, including dbt tests and automated testing practices.
Follow established schemas, data models, naming standards, and delivery patterns defined by the senior lead and enterprise architecture team.
Document models, transformations, and workflow logic as required.
Participate in Agile delivery processes and collaborate effectively across time zones within a pod-based team structure.

2+ years of experience in data engineering, analytics engineering, or closely related transformation-focused work.
Hands-on experience using dbt for data transformations in a practical project or production environment.
Strong SQL foundation, including joins, aggregations, and transformation logic.
Experience working with Snowflake or transferable experience with a similar cloud data warehouse such as Redshift.
Understanding of ETL / ELT and how raw data is transformed into usable downstream data sets.
Experience with or exposure to dbt testing and validation practices.
Ability to work within established schemas and modeling patterns rather than owning warehouse design from scratch.
Clear communication skills and enough polish to work effectively with a senior lead and distributed team.

Junior Consultant – Data Engineering

Key skills