Overview

In this Senior Data Engineer role, you own data domains end-to-end within the MarTech analytics engineering team that underpins performance marketing across Delivery Hero brands. You design and maintain pipelines and curated data models at general scale, turning diverse data into reliable datasets used for budget allocation, bidding, and model-driven decisioning. You work across BigQuery, dbt, Airflow, Pub/Sub, and Spark, partnering with stakeholders to translate needs into data contracts and reliable interfaces. You’ll drive reliability, governance, and scalable analytics that directly influence marketing effectiveness.

Compensaciones / Beneficios

- Top-notch private health insurance
- Monthly Glovo credit
- Cobee discounts on transport, food and kindergarten
- Discounted gym memberships
- Extra time off with remote work flexibility
- Enhanced parental leave

Responsabilidades

- Own data domains end-to-end from requirements to production, monitoring and daily operation
- Evolve pipeline domains (ingestion, activation, feeds, measurement curation) on Airflow, BigQuery and dbt
- Define data contracts and curated models with clear semantics and stable interfaces
- Apply dimensional/incremental modelling, historisation, partitioning and clustering
- Maintain large transformation DAGs and ensure reliability by design
- Define tests, freshness SLAs and anomaly checks to reduce incidents
- Design for idempotency, deduplication, backfills and late-arriving data
- Deliver activation and partner integrations with ad platforms (Adjust, Google, Smartly, Reddit, Pinterest, LINE, Channable, Braze)
- Handle API,



Pub/Sub and file-based ingestion (GCS, S3, CloudSQL replicas) and related failure modes
- Turn vague requests into data contracts and escalate when blocked
- Engage with staff/principal engineers on hard architectural questions
- Govern data lineage, access control, PII policy tags and GDPR-compliant handling across domains
- Review code, set standards, mentor junior team members
- Drive knowledge sharing within the chapter and Delivery Hero

Requisitos principales

- End-to-end pipeline ownership from requirements through production and maintenance
- Advanced SQL and data modelling in BigQuery (dimensional, incremental, historisation, partitioning, clustering)
- dbt model structure, tests, documentation and macros for large transformation DAGs
- Orchestration and integration: Airflow DAG design, Pub/Sub, API and file-based ingestion (GCS, S3, CloudSQL replicas); ensure idempotency and proper backfills
- Strong Python and SQL, modularisation, tests, CI/CD, version control, monitoring
- Data governance and privacy: lineage, access control, PII tags, GDPR-compliant handling in multi-entity markets
- Stakeholder partnership under ambiguity: turning vague requests into data contracts; escalate when blocked
- AI fluency and agentic workflows: leveraging LLM-driven tools to scale data engineering work
- Technical maturity: know when to decide independently vs. escalate to staff/principal engineers
- MarTech domain exposure: attribution, ad platform APIs, server-to-server flows, feeds and audience syncs

- Stakeholder collaboration
- Ambiguity tolerance
- Mentoring and knowledge sharing
- BigQuery
- dbt
- Airflow

📌 Senior Data Engineer – MarTech - Glovo (Barcelona)
🏢 Glovo
📍 Barcelona