Experteer Overview
As a Data Infrastructure Engineer at Doodle, you design, build, and operate scalable data platforms that keep data reliable, secure, and easy to use. You will collaborate with SRE, product, engineering, analytics and security teams to simplify data access and governance. The role focuses on high-throughput, distributed systems that underpin our data-driven product decisions. You’ll work with modern tooling to address complex time-sensitive data challenges and drive measurable impact across the company.

Compensaciones / Ventajas
• Design, build, and operate scalable data ingestion, transformation, storage and serving infrastructure
• Run streaming pipelines with Kafka and Avro; orchestrate batch workflows with Airflow; optimize Redshift performance and cost
• Manage secure, reproducible cloud environments via infrastructure as code and cost controls
• Own SLOs, runbooks, alerts for critical data systems; enforce data security, access controls, encryption, secrets management and retention policies
• Investigate incidents,



perform root-cause analyses, and implement preventative improvements
• Improve data discoverability through cataloging, lineage, ownership, quality testing; develop documentation, tooling, and self-service workflows for analytics and engineering teams

Responsabilidades
• 2+ years in data platform engineering or scalable software systems
• Kafka and Avro: schema design, serialization and evolution
• Redshift and production Airflow: data modeling and performance tuning
• Cloud and DevOps: CI/CD, infrastructure as code and Kubernetes, plus data lakes and open table formats
• Reliability and security: observability, incident response and debugging pipeline failures, with a security-conscious approach to data access, privacy and secrets
• Clear communication with both technical and non-technical stakeholders
• dbt: experience with it is a plus

Requisitos principales
•

📌 Data Infrastructure Engineer (Madrid)
🏢 Doodle
📍 Madrid