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SimilarWeb is seeking a Lead Data Analyst to join a three-person team that bridges data and customer-facing operations. The team handles two interconnected responsibilities: answering complex data questions that other teams cannot resolve (e.g., metric discrepancies, unexplained changes) and automating solutions so those teams can self-serve in the future.
This is an 80% hands-on, 20% management role. You will spend most of your time in data analysis while managing two direct reports: a data analyst and an analytics engineer. The position requires judgment about which recurring questions warrant automation and collaboration with the analytics engineer to build tooling, dashboards, and AI-assisted products.
Key responsibilities include:
- Running escalated data investigations end-to-end: reproducing issues, tracing numbers to source, and delivering precise answers
- Occasionally joining customer calls on urgent data issues
- Prioritizing team workload: deciding what gets answered immediately versus what gets an owner and deadline
- Setting team processes: intake, routing, ownership, and response expectations
- Turning recurring questions into permanent solutions through documentation, dashboards, and internal tools
- Managing two people, including technical direction for the analytics engineer
- Reporting findings to data-producing teams with evidence and context
- Using AI assistants (Claude, Cursor) as part of daily workflow
The role sits within a data company with many datasets. Choosing the right data source, understanding how it was built, and identifying its limits are central skills. You own the answer, not just the ticket—precision matters because customers will ask follow-up questions. You also decide when to stop answering and start building automation.
The team works in Prague's DOCK IN area with modern office facilities, though the role is hybrid.
REQUIREMENTS:
- Python is mandatory
- Strong SQL or PySpark (willingness to pick up PySpark quickly if not already proficient)
- Working experience with notebook environments, cloud platforms, and Git (stack: Databricks, AWS, GitLab)
- Software engineering knowledge sufficient to lead an engineer: version control, code review, pipelines, deployment
- Leadership experience and desire to grow in it
- Ability to work out where numbers come from and debug unfamiliar systems
- Judgment about investigation scope and analytical rigor
- Ability to explain data to non-technical audiences, including customers, precisely and clearly
- Ownership in ambiguity; problems arrive unspecified and often without an obvious owner
NICE TO HAVE:
- Experience with modeled or estimated data (panel data, web analytics, forecasting)
- Experience building or specifying AI-powered internal tools
