OverviewIn 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 / BeneficiosTop-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
ResponsabilidadesOwn 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 principalesEnd-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 (España)
🏢 Glovo
📍 España