Data Analyst
Posted 17 days ago · 85 applicants
Saving, applying or scoring takes a few seconds to set up your free account.
The role in plain words
This role involves owning end-to-end reporting, building dashboards, and analyzing funnels, attribution, and key performance metrics like CAC and LTV. Day to day, you will query and model data, collaborate with product and engineering on BI specs, and translate complex findings into actionable insights for non-technical teams.
- 4+ years in analytics, business intelligence, or a similar analytical role
- Strong SQL
- Hands-on experience with BigQuery, Presto, or similar large-scale databases/warehouses
- Hands-on experience with at least one BI tool (Looker, Tableau, Power BI, or similar)
- Experience building tables/data models and defining BI events
- Experience designing and evaluating A/B tests, including statistical significance
Extracted from the job description · kept up to date automatically
Who this suits
This role suits an experienced analyst with strong SQL skills, BI tool proficiency, and at least 4 years in data analytics or business intelligence. It is less ideal for beginners or those seeking a non-technical role focused purely on static reporting.
Full job description
Original listing · kept for referenceWe're looking for a Data Analyst to join our core team and own the data, reporting, and insight layer that our biggest decisions are built on — what to greenlight, what to spend, and where to double down. You'll report into the Head of Data and work closely with Marketing, Product, and Content, but the core of the job is data work: querying, modeling, dashboarding, and rigorous analysis. As we scale, so will your scope — this is a launchpad role, not a fixed lane.
Responsibilities
• Reporting & Dashboards: Own end-to-end reporting — build, maintain, and improve dashboards (Looker, Tableau, Power BI, or similar) — and ensure the pipelines feeding them are accurate, timely, and well-documented.
• Analysis & Insight Generation: Turn raw data into clear, actionable recommendations by analyzing funnels and attribution, tracking core KPIs (CAC, LTV, ROAS, retention), and proactively surfacing opportunities rather than waiting to be asked.
• Data Integration & Engineering: Define and validate tables and data models, define BI events and tracking specs with product and engineering, and work closely with the data engineering team to keep data clean, unified, and query-ready across analytics, ad/campaign, CRM, and product data sources.
• Experimentation: Support or run A/B tests across campaigns, product features, or content, applying statistical rigor to test design and readouts.
• Stakeholder Communication: Translate complex data into clear narratives for non-technical stakeholders, and present findings with a structured, problem-first point of view rather than just executing requests as asked.
Requirements
• 4+ years in analytics, business intelligence, or a similar analytical role.
• Strong SQL and hands-on experience with BigQuery, Presto, or similar large-scale databases/warehouses.
• Hands-on experience with at least one BI tool (Looker, Tableau, Power BI, or similar).
• Experience building tables/data models and defining BI events, ideally in partnership with data engineering.
• Experience working with digital data sources (e.g., Google Analytics, ad platforms, CRM systems).
• Solid grasp of funnels, attribution modeling, and core performance KPIs.
• Able to communicate complex data clearly to non-technical stakeholders.
• High attention to detail; structured, problem-solving mindset.
Huge Advantages
• Background in mobile / gaming / short-form content or other high-velocity B2C products.
• Experience designing and evaluating A/B tests, including statistical significance.
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- 4+ years in analytics, business intelligence, or a similar analytical role, Strong SQL, Hands-on experience with BigQuery, Presto, or similar large-scale databases/warehouses, Hands-on experience with at least one BI tool (Looker, Tableau, Power BI, or similar), Experience building tables/data models and defining BI events