5 часов назад
Data Engineer
143 100 - 186 825$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineer (Data Engineering): Building scalable analytical data models, backend systems, and data pipelines that power company-wide decisions with an accent on data quality, business rules, and analytical requirements. Focus on designing Spark and Airflow pipelines, evolving data models, integrating new data sources, and translating complex stakeholder questions into data-driven insights.
Location: San Francisco, Seattle, or Mountain View, United States, or remote. can hire in countries where it has a legal entity.
Salary: $118,773–$155,065 for Zone C, $128,790–$168,143 for Zone B, or $143,100–$186,825 for Zone A.
Company
develops software products that help teams collaborate and manage different types of work.
What you will do
- Build analytical data models, backend systems, and scalable data solutions.
- Develop and maintain data pipelines supporting finance, growth, product, customer support, sales, and marketing analytics.
- Add new data sources, implement business rules, and create metrics for business needs.
- Partner with Product, Analytics, Finance, and Operations stakeholders to translate business questions into data-driven insights.
- Own data engineering problems end to end and improve data quality and engineering practices.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Management, or another technical field, plus 4+ years of data engineering experience.
- Strong programming skills in Python or Java.
- Working knowledge of relational databases and SQL query authoring.
- Experience designing data models for efficient storage and retrieval.
- Experience building scalable pipelines with Spark or SparkSQL and Airflow or similar scheduling tools.
- Experience with Databricks and Tableau, including data storytelling and visual clarity.
Culture & Benefits
- Work from an office, from home, or through a combination of both.
- Work with a direct, collaborative data engineering team that challenges assumptions and improves solutions.
- Health and wellbeing resources.
- Paid volunteer days and additional benefits, bonuses, commissions, and equity eligibility.
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