Lead the foundational setup of new data environments, including Snowflake provisioning, SSO configuration, and initial system architecture.
Design, build, and manage scalable data pipelines and ETL/ELT processes to transform raw data into actionable insights.
Support the scaling of engineering teams to handle high volumes of commercial projects while maintaining business continuity during organizational transitions.
Develop and maintain robust DBT data models to support semantic layer build-outs and advanced analytics capabilities.
Partner closely with business leaders and stakeholders to bridge the gap between technical delivery and strategic objectives.
Provide engineering support for custom backend applications, ensuring seamless data integration and reliable exposure to end users.
Establish and enforce best practices for data engineering, architecture, and deployments that can scale across multiple organizations.

Proven experience in data engineering with a strong focus on building pipelines, supporting custom applications, and leading deployments.
Hands-on experience with Snowflake and other modern cloud data platforms such as AWS, Azure, or GCP.
Strong technical expertise in DBT for scalable data transformation, modeling, and semantic layer development.
Demonstrated ability to design and build systems from the ground up, not just extend existing infrastructure.
Advanced SQL and Python skills for complex data modeling, performance optimization, and pipeline development.
Ability to balance deep technical expertise with business acumen, confidently navigating complex stakeholder environments.
Comfortable operating in a nimble, mid-size consulting environment where priorities can shift, and adaptability is key.

Senior Data Engineer – Snowflake

Key skills