Data Engineer, AI & Analytics

This is a fully remote position, open to applicants in Spain, +1 more country.

📋 Description

• Design, develop, and uphold the essential data infrastructure, encompassing data ingestion, modeling, and data marts.

• Create robust ingestion processes to accommodate changes in ad-platform APIs, deprecated fields, rate limits, and retroactive conversion adjustments.

• Model expenditures, impressions, conversions, and revenue across platforms such as Meta, Google, TikTok, Amazon, LinkedIn, and Microsoft.

• Construct customer-level joins integrating Shopify, Klaviyo, GA4, and client CRMs.

• Contribute to custom modeling tailored for clients, incorporating unique logic, overrides, and client-specific marts.

• Develop semantic layers and metric definitions to ensure consistent AI-generated SQL outputs.

• Leverage AI-oriented workflows and coding tools to expedite development and establish smart data infrastructure.

• Document efficient AI-oriented development practices for team-wide implementation.

• Collaborate with product and engineering teams, AI/innovation, Client Service, BI, Tagging & Tracking, Data Ops, and client teams.

• Oversee and rectify data quality challenges.

• Enhance pipelines for cost efficiency and performance across a multi-client warehouse.

• Deliver production-ready datasets and pipelines that support AI, product, client, agency, BI, and internal stakeholders.

• Achieve key performance indicators related to development speed, data quality, pipeline reliability, client request handling, and cross-functional enablement.

⛳️ Requirements

• Advanced proficiency in both spoken and written English.

• Over 3 years of experience in data or analytics engineering.

• A minimum of 1 year managing a significant dbt project in a production setting.

• Advanced skills in Python and SQL.

• Extensive knowledge of dbt, including incremental strategies, Jinja, macros, packages, tests, snapshots, source freshness, exposures, DAG management, and materializations.

• Strong expertise in Snowflake and the associated cloud data ecosystem.

• Experience with modeling in a multi-tenant environment.

• Familiarity with marketing and advertising datasets, including UTMs and attribution windows.

• Proven experience in designing and overseeing end-to-end data lifecycles from ingestion to serving.

• Knowledge of cloud-native infrastructure, particularly GCP.

• Understanding of infrastructure-as-code principles.

• Experience with AI-oriented development workflows and tools like Cursor, Claude Code, and GitHub Copilot.

• Capability to design AI-ready data models, such as feature stores and semantic layers.

• Familiarity with Git and CI/CD best practices.

• Experience with automated testing processes.

• Comfortable with iterative shipping and refining data products using real-time feedback.

🏝️ Benefits

• Equal Opportunity Employer.

• A workplace committed to diversity and inclusion.

• Engagement in AI-oriented development workflows within the role.

• Opportunities to contribute to AI, product, client, and agency projects.

• Autonomy and professional development through ownership of foundational data systems.