About the team
The Marketing Data team builds the data foundation for marketing measurement and decision-making across products as part of a decentralized data ownership model. We own core marketing analytics datasets and ensure they are reliable, well documented, and usable for both reporting and advanced analysis.
We combine acquisition and product analytics data into trusted, decision-ready models and dashboards. The team is responsible for improving tracking quality, standardizing key definitions, and maintaining scalable datasets across analytics and advertising platforms.
This work helps make performance transparent and comparable across campaigns and products, enabling faster insights and more confident decision-making. You will partner with analysts, marketers, and engineers to improve data quality, evolve core metrics, and develop durable data marts that support self-serve reporting and deeper analytical use cases.
Responsibilities:
Build and maintain the Marketing Data Model (starting with GA4 and Google Ads, expanding as new sources and use cases appear).
Design and own curated datasets/marts that power self-serve analytics and dashboards (stable schemas, reusable logic).
Implement transformations using SQL (Redshift/Spectrum).
Support data investigations.
Ensure data promoted to the curated zone meets quality expectations.
Contribute to documentation and discoverability in DataHub.
Build the marketing feedback loop foundation for automated martech systems by connecting acquisition signals, user behavior, and outcomes in a scalable data layer.
Requirements:
Strong experience in analytics, analytics engineering, or another hands-on data role.
Strong SQL skills and practical experience building analytical datasets that support reporting and decision-making at scale.
Understanding of how to model data in a way that keeps definitions consistent and logic reusable across different use cases.
Comfortable partnering with both technical and business teams, and able to communicate clearly with each.
Familiarity with warehouse-based analytics environments such as Redshift, BigQuery, Snowflake, or similar.
Familiarity with modern data tooling such as Airflow, DataHub, dbt, or orchestration and cataloging tools in the same space.
Experience supporting self-serve reporting in BI tools such as Looker Studio, Tableau, Power BI, QuickSight, or similar.
Good knowledge of English and Ukrainian or Russian
Nice to have:
Experience with marketing analytics data, attribution, GA4, Google Ads, Bing or similar platforms. 
