Job Description

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.

Requirements

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.

Company offers

The opportunity to benefit from our share options programme
25 working days of holiday
Access to all the tools & tech needed for work
Home office support: we provide IT workstation equipment and a personal budget of up to 540 for home workplace furniture
Private health insurance
Confidential Employee Assistance Program (EAP) for you and your family
Frequent team-building events
A personal monthly budget for shopping on Vinted
The opportunity to spend up to 90 days per year - 21 of which can be spent working outside of the EU - on workation
A dog-friendly office
In Vilnius office: Gym & in-house meals at friendly prices
In Kaunas office: a monthly lunch allowance, and a once-a-week provided in-house lunch and breakfast