Snowflake & DBT Data Engineer

About the role We are looking for a Data Engineer with strong hands‑on experience in Snowflake and DBT to manage and optimize our data platform, supporting analytical and business operations within the asset management area.

Responsibilities

Manage Snowflake data platform environments to ensure high availability, predictable performance, and secure access for analytical and operational workloads across the organization.

Perform DBT testing on Snowflake.

Configure and optimize Snowflake Tasks to orchestrate complex data pipelines, automate recurring jobs, and maintain reliable scheduling and monitoring for critical data processes.

Administer Snowflake account‑level settings, including roles, policies, resource allocation, and usage monitoring, to support cost‑effective and compliant data operations.

Develop and maintain DBT Core projects that implement robust transformation logic, enforce data quality checks, and standardize modeling patterns for shared enterprise datasets.

Create and refine DBT macros that encapsulate reusable transformation logic, streamline project implementation, and promote consistent coding practices across multiple data teams.

Oversee DBT Cloud deployments by managing environments, jobs, and run configurations,



ensuring smooth execution of production and non‑production data workflows.

Collaborate with data engineers and analysts to translate business requirements into efficient Snowflake schemas and DBT models that enable accurate reporting and advanced analytics.

Monitor data pipeline health using platform logs and metrics, proactively troubleshoot issues, and implement remediation steps that minimize disruption to downstream consumers.

Implement robust data security and governance controls within Snowflake, including role‑based access patterns, masking policies, and audited data sharing to protect sensitive information.

Coordinate with infrastructure and application teams to integrate Snowflake and DBT with enterprise tools such as version control, monitoring platforms, and catalog solutions, supporting hybrid work arrangements.

Document platform configurations, operational runbooks, and data workflow standards in clear technical references that enable consistent administration and easier onboarding for new team members.

Drive continuous improvement by analyzing platform utilization trends, recommending optimization strategies, and implementing changes that enhance performance and reduce operational overhead.

Support asset management operations stakeholders by maintaining

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📌 Databricks Lakehouse Architect — Cloud Data Platform Leader (Madrid)
🏢 Devoteam
📍 Madrid