Vercel12 дней назад

Senior Data Engineer - Finance

14 167–21 667 ₽в месяц · до вычета

РЫНОК

14 882 ₽медиана по профессии

Data Engineer · 26 вакансий с указанной зарплатой

6 667половина предложений: 11 421–16 23421 667

В рынке · выше 46% предложений

Hybrid - San Francisco

Обязанности

01Own pipelines that bring billing, usage, and contract data into the warehouse reliably, including metered usage across multiple products
02Diagnose and resolve data quality and freshness issues at the source, not just downstream
03Design and maintain dbt models that turn raw billing and usage data into clean, trusted datasets for revenue recognition, margin, and forecasting
04Set testing and documentation standards so models hold up to the accuracy bar Finance requires when reconciling usage-based revenue against contracts
05Build datasets and semantic models that power the dashboards and reports Finance leadership uses for planning, forecasting, and close
06Reduce reliance on one-off requests by designing for self-service
07Work with Finance leaders (FP&A, Accounting, Revenue) to understand what they need from the data and why, and push back when the ask doesn't match the underlying question
08Build pipeline and transformation code to a high engineering bar, and hold others to it through code review
09Mentor other engineers and help set technical standards for the team

014+ years of experience in data engineering, analytics engineering, or a closely related field, with a track record of owning production data pipelines end-to-end
02Strong SQL and Python skills, with experience writing production-grade, testable code, not just scripts for one-off analysis
03Hands-on experience with dbt (or a comparable transformation framework), dimensional/data modeling, and modern ELT/ETL workflows, including orchestration tooling (e.g., Airflow, Dagster)
04Direct experience with Finance data, ideally including usage-based billing, revenue recognition, or financial close/forecasting metrics, with genuine fluency in how those metrics are defined and used
05Proven ability to partner with non-technical stakeholders, translating ambiguous business questions into technical specs and durable data models, not just taking requirements at face value
06Strong communication skills, including presenting technical trade-offs to both technical and business audiences
07A track record of technical ownership, with the judgment to make architecture decisions independently and mentor other engineers
08Comfort with the accuracy and auditability standards Finance data requires (e.g., reconciliation, versioning, clear lineage)

01Competitive compensation package, including equity
02Inclusive Healthcare Package
03Learn and Grow - we provide mentorship and send you to events that help you build your network and skills
04Flexible Time Off
05We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed