- Страна
- США
- Зарплата
- 155 584 $ – 320 320 $
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Staff Data Engineer, tvScientific
Высокая оценка обусловлена престижем компании Pinterest, конкурентной заработной платой и возможностью работать над сложными инженерными задачами в быстрорастущем сегменте CTV. Роль предлагает значительную автономию и влияние на стратегию.
Сложность вакансии
Роль уровня Staff предполагает высокую степень ответственности за архитектурные решения и стратегическое видение. Требуется глубокая экспертиза в Scala, Spark и AWS, а также умение работать с графами знаний и сложными API.
Анализ зарплаты
Предложенный диапазон ($155k - $320k) полностью соответствует и даже превышает рыночные стандарты для позиции Staff Data Engineer в США, особенно учитывая верхнюю границу. Это отражает высокую ценность роли для компании.
Сопроводительное письмо
I am writing to express my strong interest in the Staff Data Engineer position at tvScientific. With extensive experience in building large-scale data infrastructure using Spark and Scala, I am excited about the opportunity to evolve your core data pipelines and design efficient solutions for your massive growth in the CTV advertising space. My background in delivering APIs backed by complex datasets and my proficiency in AWS align perfectly with the technical requirements of this role.
Throughout my career, I have demonstrated a commitment to technical excellence and strategic vision, often serving as a bridge between Data Science and Product teams. I am particularly impressed by Pinterest's forward-thinking approach to AI integration and look forward to leveraging AI tools to enhance my workflow while maintaining the high standards of data integrity and verification that a Staff-level role demands. I am eager to bring my expertise in data lakes and knowledge graphs to help tvScientific continue its mission of optimizing TV advertising through data science.
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Откликнитесь в pinterest уже сейчас
Присоединяйтесь к команде Pinterest и tvScientific, чтобы создавать будущее CTV-рекламы с использованием передовых технологий обработки данных!
Описание вакансии
About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
About tvScientific
tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.
As a Staff Data Engineer at tvScientific, you will be a key player in implementing the robust data infrastructure to power our data-heavy company. You will collaborate with our cross-functional teams to evolve our core data pipelines, design for efficiency as we scale, and store data in optimal engines and formats. This is an individual contributor role, where you will work to define and implement a strategic vision for data engineering within the organization.
What you'll do:
- Design and implement robust data infrastructure in AWS, using Spark with Scala
- Evolve our core data pipelines to efficiently scale for our massive growth
- Store data in optimal engines and formats, matching your designs to our performance needs and cost factors
- Collaborate with our cross-functional teams to design data solutions that meet business needs
- Design and implement knowledge graphs, exposing their functionality both via Batch Processing and APIs
- Leverage and optimize AWS resources while designing for scale
- Collaborate closely with our Data Science and Product teams
- How we'll define success:
+ Successful design and implementation of scalable and efficient data infrastructure
+ Timely delivery and optimization of data assets and APIs
+ High attention to detail in implementation of automated data quality checks
+ Effective collaboration with cross-functional teams
What we're looking for:
- Production data engineering experience
- Proficiency in Spark and Scala, with proven experience building data infrastructure in Spark using Scala
- Experience in delivering significant technical initiatives and building reliable, large scale services
- Experience in delivering APIs backed by relationship-heavy datasets
- Familiarity with data lakes, cloud warehouses, and storage formats
- Strong proficiency in AWS services
- Expertise in SQL for data manipulation and extraction
- Excellent written and verbal communication skills
- Bachelor's degree in Computer Science or a related field
- Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
- Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
- High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables
- Nice-to-haves:
+ Experience in adtech
+ Experience implementing data governance practices, including data quality, metadata management, and access controls
+ Strong understanding of privacy-by-design principles and handling of sensitive or regulated data
+ Familiarity with data table formats like Apache Iceberg, Delta
+ Previous experience building out a Data Engineering function
+ Proven experience working closely with Data Science teams on machine learning pipelines
In-Office Requirement Statement:
- We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit ourPinFlex page to learn more about our working model.
#LI-SM4
#LI-REMOTE
At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
US based applicants only
$155,584—$320,320 USD
Our Commitment to Inclusion:
Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.
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Навыки
- Spark
- Scala
- AWS
- SQL
- Data Infrastructure
- Knowledge Graph
- API Development
- Data Lake
- Apache Iceberg
- Delta Lake
- Data Governance
Возможные вопросы на собеседовании
Для уровня Staff важно понимать, как кандидат оптимизирует затраты при работе с огромными объемами данных.
Расскажите о вашем опыте оптимизации затрат в AWS при работе с крупномасштабными Spark-кластерами. Какие стратегии вы использовали?
В описании вакансии упоминаются графы знаний как важная часть инфраструктуры.
Как бы вы спроектировали архитектуру для обслуживания графа знаний, который должен быть доступен как через пакетную обработку, так и через API в реальном времени?
Вакансия подчеркивает важность использования AI в рабочем процессе.
Как вы интегрируете инструменты AI в свой процесс разработки и как вы верифицируете результаты, чтобы избежать ошибок в критически важной инфраструктуре?
Роль требует тесного взаимодействия с Data Science.
Опишите случай, когда вам пришлось адаптировать архитектуру данных под специфические нужды команды машинного обучения. С какими трудностями вы столкнулись?
Упоминание Iceberg и Delta указывает на потребность в современных форматах хранения.
В каких сценариях вы бы предпочли Apache Iceberg вместо стандартного Parquet в S3, и как это повлияет на производительность запросов?
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- Страна
- США
- Зарплата
- 155 584 $ – 320 320 $