What we're looking for:
  • You have 4+ years of experience in data analysis.
  • You're great at talking to stakeholders, internal and external, and getting to the real question behind a request. You can then write it down as clear requirements, metric definitions and acceptance criteria.
  • You know how to design meaningful metrics and KPIs, such as engagement, retention or audience reach, and can explain their limits.
  • Excellent SQL and a solid understanding of data modelling.
  • You can build the dashboard, visualisation or table that best answers the user's question, and you know when less is more.
  • You don't take numbers at face value. You check them against the source, notice when something looks off and dig until you find out why.
  • You can present findings clearly to non-technical people, in English.
  • You share what you know with your team and with advanced users in other teams.
  • You're comfortable with technical work. Our tools are mostly open source and run by our own team, so everyone occasionally needs to troubleshoot, optimise a query, improve a process or help with an upgrade.
  • You're happy to give your opinion and question how things are done.
Nice to have:
  • Experience in product usage analytics, TV viewership analytics, or working with telecommunications and/or media companies.
  • Experience designing data models for large datasets that stay detailed enough for analysis and fast and cheap enough to query.
  • Experience with Metabase or a similar BI tool, Snowflake or another cloud data warehouse, ClickHouse, and OpenMetadata or another data catalogue.
  • Understanding data pipelines and tools that power them, such as dbt, DLT, Airflow...
  • Basic understanding of CI/CD and tools such as Jenkins, Docker and Kubernetes.
Your responsibilities:
  • Run discovery with stakeholders (Product, telco operators, media clients, management) to understand the business problem behind each request.
  • Define requirements for new data products: analytical questions, metric and KPI definitions, and acceptance criteria, written as specs or user stories for data engineers.
  • Work with Product Managers to build data awareness, promote product performance analytics and help define product usage metrics.
  • Review telemetry and event specs for new product features, so the data needed for those metrics is captured from the start.
  • Build and maintain dashboards in Metabase for internal and external users.
  • Validate data quality: check new data products against source systems and investigate anomalies and inconsistencies.
  • Handle ad-hoc analysis requests and present the findings.
  • Work alongside data engineers during builds: answer business-logic questions and test intermediate results.
  • Support advanced users in building their own queries and dashboards.
  • Add and maintain descriptions in the data catalogue (OpenMetadata).
  • Build and adjust data models that support dashboards.
We have more than cookies:
  •  Flexible working environment – we have offices in Ljubljana and Belgrade.
  • Performance bonus. 
  • Gifts for your special days. 
  • “Healthy” Friday – not always healthy snacks on Fridays. 
  • 25 vacation days.