обновлено 5 дней назад
Analytics Engineer, Data Science
117 500 - 172 800$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Analytics Engineer, Data Science (SQL/Python): Building scalable data foundations, canonical datasets, ETL/ELT pipelines, metrics, and self-serve analytics tools that support data-driven decisions across business teams with an accent on data reliability, standardization, and actionable insights. Focus on designing high-volume data pipelines, tuning SQL performance, creating visualizations, and implementing data quality checks across complex analytics domains.
Location: Austin, Chicago, New York, San Francisco, San Jose, Seattle, Los Angeles, or Washington, D.C., United States
Salary: $117,500–$172,800 USD; $143,800–$211,500 USD; or $174,400–$256,500 USD per year, plus potential equity grants.
Company
operates a technology platform for delivery and commerce, using data to support product, operations, finance, and other business functions.
What you will do
- Partner with data scientists, data engineers, and business stakeholders to translate business needs into data requirements.
- Identify business questions and develop structured analytical solutions and insights.
- Lead the development of scalable data products and self-service analytics tools.
- Build and maintain canonical datasets and reliable, high-volume ETL/ELT pipelines using data lake and data warehousing concepts.
- Design metrics, dashboards, and data visualizations using tools such as Tableau, Sigma, and Mode.
- Promote data integrity, reusability, readability, and standardization across cross-functional teams.
Requirements
- Degree in mathematics, physics, statistics, economics, computer science, or a similar field.
- 2–6+ years of experience in business intelligence, analytics engineering, data engineering, or a similar role.
- Strong SQL skills and proficiency in at least one functional or object-oriented language, such as Python or Scala.
- Experience creating reporting and data visualization solutions with tools such as Looker, Tableau, or Sigma.
- Knowledge of database and data processing technologies including S3, Trino, Hive, or Spark, plus SQL performance tuning experience.
- Experience writing data quality checks and communicating with both technical and non-technical teams.
Culture & Benefits
- Cross-functional work across Analytics, Data Engineering, Product, Operations, Finance, and other business areas.
- 401(k) plan with employer matching.
- Medical, dental, and vision insurance, disability and basic life insurance, and mental health support.
- Sixteen weeks of paid parental leave, family-forming assistance, wellness benefits, and commuter benefits matching.
- For salaried roles, flexible paid time off and 80 hours of paid sick time per year, plus 11 paid holidays.
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