Salary
💰 €40,000 - €50,000 per year
Tech Stack
BigQueryPythonSQLTableau
About the role
- Cross-Functional Data Partnering: Collaborate with Product, Marketing, Operations, and Finance to define and align on KPIs and business metrics. Provide actionable insights that support strategic and operational decision-making.
- Metrics Definition & Governance: Audit existing dashboards, data sources, and definitions to resolve inconsistencies and streamline reporting. Own and maintain documentation of source-of-truth metrics and definitions across teams.
- Data Infrastructure & Quality Oversight: Partner with Data Engineering and Operations to address broken data pipelines or unreliable sources. Escalate and prioritize data quality issues that impact performance or decision-making.
- Strategic Analysis & Business Impact: Lead high-impact, cross-functional analyses related to growth, operations, or user behavior. Bring clarity to ambiguous questions through structured analysis and data storytelling.
- Enablement & Communication: Serve as the go-to person for data requests, stakeholder questions, and internal education. Identify and promote opportunities for scalable reporting practices and tooling improvements.
Requirements
- 5–10 years of experience in data analysis, analytics engineering, or similar roles.
- Expert SQL skills and experience working directly with data warehouses (e.g., BigQuery, Snowflake).
- Proven track record of owning complex, cross-functional projects end-to-end.
- Strong business acumen with the ability to translate insights into strategic action.
- Experience documenting and managing KPIs, dashboards, or data models.
- Excellent communication skills, both technical and business-facing.
- Fluency in English.
- Familiarity with AI-powered analytics tools (e.g., GPT-based insights, automated dashboards). (Nice-to-have)
- Understanding of how generative AI and ML models can enhance internal workflows. (Nice-to-have)
- Experience with dbt, Looker, Tableau, or other BI and modeling tools. (Nice-to-have)
- Knowledge of Python, R, or scripting for light automation or statistical tasks. (Nice-to-have)
- Background in operations, e-commerce, or B2B SaaS environments. (Nice-to-have)
- Experience in high-growth or early-stage companies. (Nice-to-have)
- Familiarity with experimentation frameworks (e.g., A/B testing, lift analysis). (Nice-to-have)