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Senior Data Engineer

Оценка ИИ

Mozilla — престижный работодатель с сильной миссией и отличным социальным пакетом. Удаленный формат работы по всему миру и фокус на открытом ПО делают эту вакансию крайне привлекательной.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует глубоких знаний SQL, Python и опыта работы с облачными системами (GCP). Высокая планка ответственности за качество данных и участие в дежурствах (triage rotation) повышают сложность.

Анализ зарплаты

Медиана165 000 $
Рынок135 000 $ – 200 000 $
Оценка ИИ

Зарплата в Mozilla обычно соответствует верхнему сегменту рынка для Senior-позиций в США и Европе. Учитывая отсутствие конкретных цифр в объявлении, мы опираемся на рыночные данные для Senior Data Engineer в крупных технологических компаниях. Пакет включает значительные бонусы и пенсионные отчисления, что повышает общую ценность предложения.

Сопроводительное письмо

I am writing to express my strong interest in the Senior Data Engineer position at Mozilla. As a long-time advocate for the open web and a frequent Firefox user, I am deeply inspired by Mozilla’s mission to reclaim an internet built for people. With over four years of experience in data engineering, I have developed a robust skill set in Python and SQL, and I am particularly excited about your recent initiatives like the medallion architecture and data observability.

In my previous roles, I have successfully managed complex data lifecycles, transforming raw telemetry into high-quality analytical models. I have extensive experience with GCP and distributed systems, and I pride myself on writing modular, reusable code that maintains performance at scale. I am also eager to integrate AI into data engineering workflows, aligning with Mozilla's forward-thinking approach to scaling technical operations.

I am a self-directed engineer who thrives in distributed teams and values incremental delivery. I look forward to the possibility of contributing to the Data Engineering team and helping Mozillians make data-informed decisions that shape the future of the internet.

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Описание вакансии

To learn the Hiring Ranges for this position, please select your location from the Apply Now dropdown menu.

To learn more about our Hiring Range System, please click this link.

Why Mozilla?

Mozilla Corporation is the non-profit-backed technology company that has shaped the internet for the better over the last 25 years. We make pioneering brands like Firefox, the privacy-minded web browser. Now, with more than 225 million people around the world using our products each month, we’re shaping the next 25 years of technology and helping to reclaim an internet built for people, not companies. Our work focuses on diverse areas including AI, social media, security and more. And we’re doing this while never losing our focus on our core mission – to make the internet better for people. 

The Mozilla Corporation is wholly owned by the non-profit 501(c) Mozilla Foundation. This means we aren’t beholden to any shareholders — only to our mission. Along with thousands of volunteer contributors and collaborators all over the world, Mozillians design, build and distribute open-source software that enables people to enjoy the internet on their terms. 

About this team and role:

As a Senior Data Engineer at Mozilla, you will be a key member of our Data Engineering team. This team manages the entire data lifecycle: ingesting and transforming raw data into reliable, high quality models that empower Mozillians to make data informed decisions. 

You’ll bridge the gap between our technical systems and our business needs, helping us build a better data platform while making sure the data itself is easy for other teams to use and trust. Recent platform improvements the team has driven include launching a data catalog, introducing data observability, and implementing a medallion architecture to ensure our data is reliable, accurate, and accessible. Check out theData@Mozilla blog for more details on our work.

What you’ll do:

  • Build the pipes: You’ll build and manage our business data pipelines as well as transform Firefox telemetry data into structured high quality datasets Mozillians can rely on
  • Make data make sense: You’ll partner with data scientists, product, and marketing teams to turn complex datasets into the models and metrics that drive Mozilla’s decisions
  • Be a guardian of data quality: You’ll ensure our datasets stay accurate and performant by using our observability tools to monitor quality and joining a weekly triage rotation to resolve data issues as they arise
  • Evolve our platform: You’ll partner with other data engineers and platform engineers to improve how we work
  • Maintain data integrity: You’ll ensure our data governance and privacy policies are implemented and enforced across the tens of terabytes of data flowing through our systems daily

What you’ll bring:

  • Experience: At a minimum, 4 years of professional experience in data engineering
  • Technical skills: Proficiency in SQL and Python, and an eagerness to integrate AI into data engineering workflows to help us scale
  • Data modeling:Experience mapping complex business processes into extensible, analytical data models. You have a clear vision for long-term architecture but prefer an incremental approach that delivers immediate value while allowing our models to evolve.
  • Strong software engineering fundamentals: You build modular, reusable code and efficient logic that remains performant when processing data at our scale
  • Self directed execution: You are comfortable taking a high level goal and turning it into a plan. You have a track record of owning projects from start to finish, managing your own blockers, and keeping your team in the loop.
  • Collaborative spirit: You possess strong communication skills and the ability to work effectively with a distributed team across different time zones.
  • Our team requires skills in a variety of domains. You should have proficiency in one or more of the areas listed below, and be interested in learning about the others:
  • A track record of recommending and implementing new data collection methods to improve data model quality
  • You have used data to answer specific questions and guide company decisions.
  • You have experience with cloud distributed systems (we use GCP) including distributed databases, message queues or batch / stream processing
  • You ensure data is safe to depend on through smart orchestration, error handling, and idempotency
  • Commitment to our values:
  • Welcoming differences
  • Being relationship-minded
  • Practicing responsible participation
  • Having grit

What you’ll get:

  • Generous performance-based bonus plans to all eligible employees - we share in our success as one team
  • Rich medical, dental, and vision coverage
  • Generous retirement contributions with 100% immediate vesting (regardless of whether you contribute)
  • Quarterly all-company wellness days where everyone takes a pause together
  • Country specific holidays plus a day off for your birthday
  • One-time home office stipend
  • Annual professional development budget
  • Quarterly well-being stipend
  • Considerable paid parental leave
  • Employee referral bonus program
  • Other benefits (life/AD&D, disability, EAP, etc. - varies by country)

About Mozilla

Mozilla exists to build the Internet as a public resource accessible to all because we believe that open and free is better than closed and controlled. When you work at Mozilla, you give yourself a chance to make a difference in the lives of Web users everywhere. And you give us a chance to make a difference in your life every single day. Join us to work on the Web as the platform and help create more opportunity and innovation for everyone online.

Commitment to diversity, equity, inclusion, and belonging

Mozilla understands that valuing diverse creative practices and forms of knowledge are crucial to and enrich the company’s core mission.  We encourage applications from everyone, including members of all equity-seeking communities, such as (but certainly not limited to) women, racialized and Indigenous persons, persons with disabilities, persons of all sexual orientations, gender identities, and expressions.

We will ensure that qualified individuals with disabilities are provided reasonable accommodations to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment, as appropriate. Please contact us at hiringaccommodation@mozilla.com to request accommodation.

We are an equal opportunity employer. We do not discriminate on the basis of race (including hairstyle and texture), religion (including religious grooming and dress practices), gender, gender identity, gender expression, color, national origin, pregnancy, ancestry, domestic partner status, disability, sexual orientation, age, genetic predisposition, medical condition, marital status, citizenship status, military or veteran status, or any other basis covered by applicable laws.  Mozilla will not tolerate discrimination or harassment based on any of these characteristics or any other unlawful behavior, conduct, or purpose.

Group: D

#LI-DNI

Req ID: R3080

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Навыки

  • SQL
  • Python
  • Google Cloud Platform
  • Data Modeling
  • Data Pipelines
  • Distributed Systems
  • Software Engineering
  • Data Governance
  • Data Observability

Возможные вопросы на собеседовании

Проверка понимания архитектурных паттернов, упомянутых в описании вакансии.

Расскажите о вашем опыте работы с medallion architecture. Какие преимущества и сложности вы видите в разделении данных на слои Bronze, Silver и Gold?

Вакансия подчеркивает важность качества данных и наблюдаемости.

Как бы вы организовали систему мониторинга и алертинга для пайплайна, обрабатывающего терабайты данных ежедневно?

Mozilla использует Google Cloud Platform.

Опишите ваш опыт работы с распределенными системами в GCP (например, BigQuery, Dataflow или Pub/Sub). Как вы обеспечиваете идемпотентность при обработке данных?

Проверка навыков проектирования моделей данных.

Как вы подходите к проектированию аналитических моделей для сложных бизнес-процессов, чтобы они оставались расширяемыми и производительными?

В описании упоминается интеграция ИИ в рабочие процессы.

Как, по вашему мнению, инструменты ИИ могут быть эффективно интегрированы в повседневную работу Data Engineer для повышения продуктивности или качества кода?

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