AI-Driven Data Engineer for Analytics & Pipelines

Power Digital Marketing; España; On-site; EUR 65,000 - 100,000; Full time

Job summary

Power Digital Marketing seeks a Data Engineer to own end-to-end data pipelines, modeling, and data marts supporting agency teams and AI initiatives. You will work across ingestion, semantic layers, and AI-ready data solutions in a multi-client environment.

Strong production-grade Python/SQL, dbt expertise, Snowflake and GCP know-how are required, with experience in CI/CD and data quality management.

Qualifications

• 3+ years in data/analytics engineering.
• Advanced proficiency in Python and SQL for production-grade data pipelines.
• Deep expertise in dbt including incremental strategies, tests, and snapshots.
• Strong command of Snowflake and cloud data stack.
• Experience modeling in a multi-tenant environment.

Responsibilities

• Design, build, and maintain core data foundation (ingestion, modeling, data marts) from raw platform data to serving layers.
• Build ingestion handling API changes, deprecated fields, rate limits, and retroactive restatement.
• Model across sources for reconciled spend, impressions, conversions, revenue across major platforms and client CRMs.
• Contribute to client-bespoke modeling on top of core layer with patterns extended across clients.
• Build semantic layers and metric definitions for AI-generated SQL to be reliable.
• Use AI-agentic workflows to accelerate development and document patterns.
• Collaborate with nova product/engineering, AI/innovation, and client teams to translate requirements into data solutions.
• Monitor data quality and optimize pipelines for cost and performance.

Skills

Python

SQL

dbt

Snowflake

GCP

AI agentic workflows

Git

CI/CD

Tools

dbt

Job description

Power Digital Marketing seeks a Data Engineer to own end-to-end data pipelines, modeling, and data marts supporting agency teams and AI initiatives. You will work across ingestion, semantic layers, and AI-ready data solutions in a multi-client environment.

Strong production-grade Python/SQL, dbt expertise, Snowflake and GCP know-how are required, with experience in CI/CD and data quality management.