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Software Engineer, Data Platform
Отличная вакансия в престижном хедж-фонде с сильным социальным пакетом и работой над передовыми технологиями (AWS, Databricks). Локация в Варшаве предлагает конкурентную среду и возможности для профессионального роста.
Сложность вакансии
Высокая сложность обусловлена требованиями к глубоким знаниям Spark Streaming, Kubernetes и опыта работы с платформой Databricks в контексте финансовых данных. Роль подразумевает лидерские качества и владение современными архитектурными паттернами (microservices, event-driven).
Анализ зарплаты
Предлагаемая позиция соответствует уровню Senior/Lead в Польше. Рыночные оценки для таких ролей в международном финтехе в Варшаве обычно начинаются от 25 000 PLN и могут достигать 35 000 PLN и выше в зависимости от бонусов.
Сопроводительное письмо
I am writing to express my strong interest in the Software Engineer, Data Platform position at Point72. With over three years of experience in Python and a deep focus on building scalable data pipelines using PySpark and AWS, I am confident in my ability to contribute to your multitenant data platform. My background in microservices and event-driven architectures aligns perfectly with your team's mission to streamline data ingestion and consumption.
Throughout my career, I have gained extensive experience with Databricks, Delta Lake, and Kubernetes, which are central to your current technology stack. I am particularly drawn to Point72's commitment to innovation and the use of open-source solutions to solve complex financial data challenges. I am eager to bring my technical expertise and proactive problem-solving approach to your Warsaw-based engineering team.
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Откликнитесь в point72 уже сейчас
Присоединяйтесь к команде Point72 в Варшаве и создавайте будущее финансовых технологий на базе AWS и Databricks!
Описание вакансии
A Career with Point72’s Technology Group
As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity.
We’re looking for individuals that are highly proficient in their respective technology platform, articulate, solution driven, client focused, and proactive in building their technology skills.
What you’ll do
You will be part of the team that builds a multitenant data platform to onboard internal and external data sources and perform a central role in data ingestion, consumption, and cataloguing. You will join a team of experts in data pipelines focusing on data streaming and acquisition, storage of the data in multiple forms (raw, normalized, operational vs historical), ELT, transformation, distribution, access layers for different types of technical access and entitlements. Building and enhancing our data platform includes applying data lake components with raw data, joined operational data, a warehouse for history and API, and an access layer, across on prem and cloud technologies and clients. In this role, you will be responsible for leading and providing best practices for the team managing the Data Platform on AWS for our Firm. You will work closely with the architect/business for gathering requirements and delivering. As a Lead Python Engineer, you will be:
• Working together with Engineering Managers and the rest of Leadership team in Poland and US
• Planning projects and successfully delivering them with the team
• Building data ingestion pipelines in the cloud and assisting in extending our AWS cloud offering
• Working extensively in Databricks platform and leveraging all of the Databricks features (pipelines, Unity Catalogue, streaming, etc)
• Improving excellence of the team, processes, and practices within the company
• Working with customers towards a project’s success
What’s required
The ideal candidate should be experienced in Python and AWS Cloud with good communication skills.
• Excellent Python and software craftsmanship skills (more than 3 years)
• Experience with working in microservices framework and event-driven architectures
• Experience with Spark (building scalable and maintainable pipelines in PySpark and Scala)
• Experience with Spark Streaming (building low latency pipelines)
• Experience with Delta format (opensource Delta Lake project)
• Experience with Kubernetes
• Experience with MongoDB
• Experience with AWS Cloud
• Commitment to the highest ethical standards
We take care of our people
We invest in our people, their careers, their health, and their well-being. When you work here, we provide:
• Sports card
• Private life insurance
• Private medical and dental care, with vision allowance
• Private pension scheme
• Volunteer opportunities
• Support for employee-led affinity groups representing women, people of color and the LGBT+ community
• Business travel accident insurance
• Employee assistance program
• Educational assistance reimbursement
About Point72
Point72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit www.Point72.com/working-here
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Навыки
- Python
- AWS
- Databricks
- Apache Spark
- PySpark
- Scala
- Kubernetes
- MongoDB
- Delta Lake
- Microservices
- Event-Driven Architecture
- ETL
Возможные вопросы на собеседовании
Проверка опыта работы с ключевым инструментом платформы.
Расскажите о вашем опыте оптимизации производительности Spark-задач в среде Databricks. С какими узкими местами вы сталкивались?
Важно для понимания навыков работы с данными в реальном времени.
Как вы обеспечиваете отказоустойчивость и семантику 'exactly-once' при построении Spark Streaming пайплайнов?
Проверка архитектурного мышления в рамках облачной инфраструктуры.
Опишите процесс проектирования микросервиса для обработки данных в AWS с использованием Kubernetes и MongoDB. Как вы организуете взаимодействие между сервисами?
Оценка понимания современных форматов хранения данных.
В чем основные преимущества использования Delta Lake по сравнению с обычным Parquet в контексте ACID-транзакций и управления версиями данных?
Проверка лидерских качеств и умения работать в команде.
Как вы подходите к внедрению лучших практик разработки (best practices) в команде и контролю качества кода?
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