As an Analytics Engineer in Marketing, you’ll architect, scale, and optimize the business critical marketing data pipelines that teams rely on to optimize marketing performance and decision-making. Specifically, you will design 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.
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.
We have three distinct roles within Data Science & Analytics (DSA). We believe each role can make a similar business impact in different ways, and therefore our salary ranges are the same for all three roles. To understand your role within DSA context better, here are brief descriptions of each role we have in the department:
- Analytics Engineers are responsible for data curation – translating data needs from stakeholders into architecting, building and maintaining efficient & reliable data models and pipelines.
- Decision Scientists are responsible for actionable insights, identifying and sizing opportunities, and automated tools that increase the quality of product and business decisions by applying statistical methods and data-driven decision-making.
- Data Scientists are responsible for identifying algorithmic opportunities, ensuring those opportunities are addressed optimally, and designing, developing, and maintaining production-grade statistical and machine learning algorithms.
- Architect 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.
- Standardize and scale testing practices across marketing pipelines by implementing automated anomaly detection and regression checks 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.
- Proactively identify and drive opportunities to enhance the impact of Data Science and Analytics at Vinted.
