Senior
Lead analytics engineering for Reddit's Sales & Marketing data foundation
Reddit is hiring a Senior Analytics Engineer to sit at the intersection of Data Science and Data Engineering, owning data pipelines, ETLs, and self-service tooling for the Sales and Marketing org. The role requires an advanced quantitative degree plus 4-5+ years of large-scale ETL experience, strong Python/SQL/Spark skills, and dashboard/visualization craft (Looker, Tableau, D3). Expect questions on pipeline architecture, data governance, and driving org-wide adoption of self-service analytics.
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What this interview tests
- Large-scale ETL/ELT pipeline design and data modeling
- Data governance and quality at structured/unstructured scale
- Self-service analytics tooling and dashboard design (Looker, Tableau, D3)
- Sales & Marketing domain data needs (advertiser outreach, campaign tracking)
- Mentorship and cross-functional stakeholder communication
Common question themes
Design an ETL pipeline that ingests advertiser and campaign data and needs to remain reliable and maintainable for years.
How do you approach data governance when data producers and data consumers have very different technical fluency?
Walk through a self-service dashboard or tool you built that drove real adoption — how did you measure that?
How do you use Airflow (or similar) to manage dependencies and failure recovery across a large pipeline DAG?
Tell me about a time you mentored a junior data scientist or analytics engineer through a technical problem.
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