Senior MarTech Data Engineer: End-to-End Pipelines

Delivery Hero; Vilanova y Geltrú; On-site; EUR 90,000 - 120,000; Full time

Benefits offered by this job

Private health insurance

Monthly Glovo credit

Cobee discounts

Discounted gym memberships

Remote work 2 days/week

Extra time off

Job summary

Glovo, part of the Delivery Hero Group, is seeking a Senior Data Engineer to own MarTech analytics platforms end-to-end, including ingestion pipelines, data quality, and contracts that stakeholders rely on for budget or bidding decisions.

You will work across BigQuery, dbt, Airflow, Pub/Sub and Spark at scale, shaping the data foundation used by performance marketing across Glovo and the Delivery Hero group.

Qualifications

• End-to-end pipeline ownership: taking a data domain from requirements through production, monitoring and daily maintenance.
• Advanced SQL and data modelling: deep BigQuery skills, dimensional and incremental modelling, historisation, partitioning and clustering, and the judgment to know when each applies.
• dbt and transformation frameworks: model structure, tests, documentation and macros, keeping a large transformation DAG maintainable.
• Orchestration and integration patterns: Airflow DAG design, Pub/Sub, API and file-based ingestion (GCS, S3, CloudSQL replicas), idempotency, deduplication, backfills and late-arriving data.
• Software engineering practice: strong Python and SQL with modularisation, testing, CI/CD, version control and monitoring.
• Data governance and privacy: lineage, access control, PII policy tags and GDPR-compliant handling in a multi-entity, multi-market environment.
• Stakeholder partnership under ambiguity: turning vague requests from data scientists, analysts and marketing teams into data contracts, escalating when blocked, and pushing back on the wrong request.
• AI fluency and agentic workflows: using LLM-driven or tool-using agents to scale data engineering work, with a clear view of where they help and where they do not.
• Technical maturity: knowing when to decide and when to reach up to staff and principal engineers, and distinguishing your own contribution from the team’s outcome.
• MarTech domain exposure: attribution, ad platform APIs, server-to-server conversion flows, feeds and audience syncs. A plus, not a requirement.

Responsibilities

• Own and evolve pipeline domains (ingestion, server-to-server activation, feeds, measurement curation) on Airflow, BigQuery and dbt, from design and architecture through rollout and ongoing maintenance.
• Take a domain from requirements to production, monitoring and daily operation, rather than handing it over at deployment.
• Balance engineering rigour against business constraints and timelines.
• Design the curated layer others build on.
• Design and maintain the curated models that budget allocation, bidding and data science models consume, with clear contracts, documented semantics and stable interfaces.
• Apply dimensional and incremental modelling, historisation, partitioning and clustering, and judge when each applies.
• Keep a large transformation DAG maintainable as scope and team size grow.
• Make reliability the default, not the reaction.
• Define tests, freshness SLAs and anomaly checks across owned domains, reducing incident rate and time-to-detect instead of reacting after stakeholders notice.
• Design for idempotency, deduplication, backfills and late-arriving data.
• Improve runtime, cost and backfill behaviour of owned pipelines, with measurable before and after numbers.
• Deliver activation and partner integrations.
• Build reliable outbound flows to ad platforms (Adjust, Google, Smartly, Reddit, Pinterest, LINE, Channable, Braze), where correctness directly moves marketing spend.
• Handle API, Pub/Sub and file-based ingestion (GCS, S3, CloudSQL replicas) and the failure modes each brings.
• Translate vague requests from data scientists, analysts and marketing teams into defined data contracts, escalating when blocked and pushing back on the wrong ones.
• Reach up to staff and principal engineers on hard architectural questions rather than working in isolation.
• Own lineage, access control, PII policy tags and GDPR-compliant handling across your domains.
• Raise the engineering bar.
• Review code, set standards, and mentor junior members of the chapter.
• Drive knowledge sharing within the chapter and across Delivery Hero.

Skills

Advanced SQL

Data modelling

Dimensional modelling

Incremental modelling

Historisation

Partitioning

Clustering

Python

Monitoring

Tools

Airflow

BigQuery

dbt

Pub/Sub

Spark

GCS

S3

CloudSQL

Job description

Glovo, part of the Delivery Hero Group, is seeking a Senior Data Engineer to own MarTech analytics platforms end-to-end, including ingestion pipelines, data quality, and contracts that stakeholders rely on for budget or bidding decisions.

You will work across BigQuery, dbt, Airflow, Pub/Sub and Spark at scale, shaping the data foundation used by performance marketing across Glovo and the Delivery Hero group.