- Company Name
- Tailscale
- Job Title
- Analytics Engineer, Data
- Job Description
-
Job Title: Analytics Engineer, Data
Role Summary: Design, build, and maintain scalable data models and pipelines that empower Finance, Engineering, Sales, Product, Marketing, and Customer Success teams to make data‑driven decisions.
Expectations:
- Own end‑to‑end data solutions, from ingestion to transformation, quality, documentation, and stakeholder enablement.
- Act autonomously, prioritising high‑impact problems and balancing trade‑offs in a fast‑paced environment.
- Deliver clean, maintainable code and robust automated workflows that replace manual, ad‑hoc processes.
Key Responsibilities:
- Partner with cross‑functional stakeholders to uncover workflows, data needs, and pain points across billing, finance, product, GTM, and operations.
- Design, develop, and maintain dbt models and data pipelines in Snowflake, ensuring accuracy for financial reporting (ARR, billing, revenue recognition) and operational analytics.
- Resolve ambiguous, high‑complexity problems by untangling systems, clarifying logic, and producing durable solutions.
- Translate incomplete requirements into structured models, automated workflows, and end‑to‑end deliverables.
- Advocate and enforce high standards of data quality, clarity, documentation, and maintainability.
- Identify connections between domains, simplify processes, standardize practices, and surface automation opportunities.
Required Skills:
- Advanced SQL proficiency and modern data modeling expertise.
- Hands‑on experience building production‑grade data pipelines (dbt, Snowflake, Prefect, or similar).
- Proven track record converting manual workflows into automated, durable pipelines or self‑service solutions.
- Strong communication and collaboration skills, able to bridge technical and non‑technical audiences.
- Comfortable working independently, making thoughtful trade‑offs, and challenging assumptions defensively.
- Generalist mindset with interest in finance, product, GTM, and operations data challenges.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Data Science, Finance, or related field, or equivalent practical experience.
- Relevant certifications (e.g., Snowflake, dbt, or other data engineering tools) are a plus.