Waymo предлагает отличную возможность с четкой ролью в области инженерии данных, высокой зарплатой выше рыночных ставок и акцентом на инновационных технологиях автономного вождения.
Высокая зарплата
Продуктовая компания
Четкие обязанности
Мэтч & Сопровод
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Senior Data Engineer (Data Warehousing and Pipelines): Building scalable data models, warehouses, and pipelines for Waymo commercialization tracking and optimization with an accent on analytical data modeling, data quality, governance, and PII protection. Focus on transforming raw data for reporting, optimizing BigQuery and Snowflake solutions, and designing complex data engineering architectures.
Location: Onsite in Mountain View, California, United States
Base salary: $251,000–$310,000 USD per year, plus eligibility for an annual bonus, equity incentive plan, and company benefits.
Company
Autonomous driving technology company building the Waymo Driver and fully autonomous ride-hail services.
What you will do
Translate business requirements into conceptual, logical, and physical data models.
Define core data concepts for commercialization and implement them in databases.
Design, build, and maintain data warehouses and data pipelines.
Transform raw data into reliable datasets for reporting, insights, tracking, and optimization.
Implement data quality frameworks, documentation, PII handling, and access-control lists.
Collaborate with data producers and consumers across the organization to align data solutions with business needs.
Requirements
6+ years of professional experience in data engineering or a related field.
Experience delivering complex data engineering architectures from conception through deployment.
Experience designing data warehouses or data lakes with technologies such as BigQuery and Snowflake.
Deep knowledge of relational and NoSQL databases, scalable data modeling, data quality frameworks, and data governance.
Proficiency in SQL and familiarity with Python, C++, or Java.
Ability to work onsite in Mountain View, California.
Nice to have
Experience with Spark, Hadoop, Kafka, or other distributed processing tools for large-scale real-time or batch analytics.
Strong understanding of data privacy, security, quality, correctness, and efficiency tradeoffs.
Experience leading projects and collaborating across organizational boundaries and cross-functional teams.
Culture & Benefits
Collaborative work with data producers, data consumers, and cross-functional stakeholders.
Discretionary annual bonus program, subject to eligibility.
Equity incentive plan, subject to eligibility.
Company benefits program, subject to eligibility.
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