Revenue & Orders Analytics Engineer

Vinted; Amsterdam; Hybrid; EUR 54,000 - 73,000; Full time

Benefits offered by this job

Share options programme

25 days paid annual leave

Newest MacBook models

Employee Assistance Program (EAP)

Team-building events

Home office budget €540 for furniture

Lunch benefit

Job summary

Vinted is seeking an Analytics Engineer to join the Revenue, Purchase & Order Analytics Engineering team. You will build scalable data products and pipelines powering analytics, ML use cases, and decision-making across revenue, purchase, and orders.

You will embed testing and quality controls, strengthen observability, and own production data systems from incidents to durable fixes, in a hybrid work environment across Europe.

Qualifications

• Experience as Analytics Engineer, Data Engineer, or closely related data role.
• Strong SQL and data warehousing fundamentals for clean, performant data solutions.
• Hands-on with dbt or similar data transformation framework.
• Experience with a cloud data warehouse (BigQuery, Snowflake, Redshift, or similar).
• Solid understanding of data modelling principles and their application to real-world analytics.
• Familiarity with workflow orchestration tools (Airflow, Dagster, or similar).
• Comfortable with high-volume, critical data and a bias for action.
• Strong communication in English to explain technical concepts clearly.

Responsibilities

• Build scalable data products and pipelines powering analytics and ML use cases.
• Embed automated testing, validation, and quality controls across the data lifecycle.
• Improve observability with monitoring and alerting to catch issues early.
• Own end-to-end production data systems and implement durable fixes for resilience.

Skills

SQL

dbt

BigQuery

Snowflake

Redshift

Data Modeling

Airflow

English Proficiency

Tools

Cloud Data Warehouse

BI Tools

Job description

Vinted is seeking an Analytics Engineer to join the Revenue, Purchase & Order Analytics Engineering team. You will build scalable data products and pipelines powering analytics, ML use cases, and decision-making across revenue, purchase, and orders.

You will embed testing and quality controls, strengthen observability, and own production data systems from incidents to durable fixes, in a hybrid work environment across Europe.