As an Analytics Engineer in Marketing, you’ll design, build and maintain the business critical marketing data pipelines that teams rely on to optimize marketing performance and decision-making. Specifically, you will develop robust, future-proof pipelines that ingest, process, and monitor data from diverse external sources to ensure our teams have access to high-integrity data. In this role, you’ll have the opportunity to build a deep understanding of the marketing domain while proactively identifying data-related process optimization opportunities.

As an Analytics Engineer in Marketing, you’ll design, build, and operate the marketing data pipelines that teams rely on to optimize marketing performance and decision-making.

You’ll partner closely with:

• Marketing Operations Intelligence and Marketing Modelling Intelligence teams, who use this data daily for performance reporting and model-driven optimisation.
• Other Analytics Engineers in Marketing, with shared ownership of the marketing data domain
• A broader 40+ person Analytics Engineering Guild across Vinted, where you’ll benefit from established patterns, code reviews, reusable dbt and python components, and regular knowledge sharing.

This is an end-to-end role across BigQuery, dbt, Airflow: from raw ingestion and transformations through to trusted, well-documented datasets and domain-ready reporting.

You will report to the Manager of Data Science & Analytics, Marketing Analytics Engineering.

• Design and build scalable and reliable marketing data models in dbt/BigQuery/Looker that turn marketing operations and modelling data into Decision-ready datasets used for reporting, analysis and optimization.
• Implement data quality checks and controls (tests, regressions, anomaly detection) to increase reliability and consistency of reporting.
• Own production reliability by investigating incidents end-to-end, performing root-cause analysis, and shipping fixes that prevent repeat failures.
• Translate Marketing needs into clear technical delivery by gathering requirements in plain language, aligning definitions and turning them into documented models and metrics.
• Drive adoption and correct usage by writing practical documentation, enabling self-serve analysis.

• Hands-on experience in Analytics Engineering or Data Engineering (typically around 3 years), or a closely related role with ownership of production pipelines. 
• Strong SQL skills, including writing readable, maintainable queries and improving performance when datasets scale.
• Hands-on dbt experience, including building obvious, well-tested and performant models. Experience with the rest of our stack is a plus (Google Cloud Platform, Airflow, Python, Looker)
• Working knowledge of Git and collaboration practices (pull requests, code reviews, version control).
• Strong attention to detail, including validating outputs (tests/reconciliations), catching edge cases and keeping metric definitions consistent and well-documented.
• Problem-solving and optimization mindset.
• Strong communication and collaboration skills, with the ability to build and maintain cross-functional relationships and translate business needs into technical solutions.
• Excellent verbal and written communication skills in English.

• The opportunity to benefit from our share options programme
• 25 days of paid annual leave
• Newest MacBook models
• Confidential Employee Assistance Program (EAP) for you and your family
• Frequent team-building events
• Home office support: we provide IT workstation equipment and a personal budget of up to €540 for home workplace furniture
• Lunch benefit per working day
• Company bike leasing scheme
• Monthly budget for a flexible benefits platform
• Work from Home allowance
• Access to a discounted gym membership plan
• A personal monthly budget for shopping on Vinted
• Collective Defined Contribution Pension plan
• NS Business Card for your commute to the office by public transport
• A dog-friendly office

Workation Policy

Better balance holidays with workdays by working remotely! Up to 90 days per year in the EU, of these, 21 days can be spent globally. For non-EU citizens, it's 21 days worldwide. This can be combined with time off for vacation or personal time.

Individual Learning Budget

Each year, you’ll be given a learning budget (starting at €3,000), and a total of up to 10 working days over a 2-year period to support your personal and professional development.

Hybrid Work 

Our hybrid model, with 2 recommended office days a week, gives you and your team the flexibility to decide if and when you want to work from home, and when to catch up in person.

Equal Opportunity

We welcome applications from everybody, regardless of your background, identity, or life experiences. Job openings come with guides, not checklists. If you’re excited about a role, but don’t identify with every point in the ‘About you’ section, apply anyway – you might still be the perfect match!