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Staff Analytics Engineer

Оценка ИИ

AlphaSense — быстрорастущий 'единорог' в сфере AI и FinTech с сильной инженерной культурой. Позиция предлагает работу с современным стеком (GCP, AWS, K8s) и прямое влияние на продукт, используемый компаниями из S&P 500.


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Сложность вакансии

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Оценка ИИ

Роль уровня Staff требует не только глубоких технических знаний Python, GCP и AWS, но и умения проектировать сложные архитектуры данных и работать с Kubernetes. Высокая планка ответственности за R&D Data Lake делает позицию сложной и стратегически важной.

Анализ зарплаты

Медиана65 000 $
Рынок50 000 $ – 85 000 $
Оценка ИИ

Зарплата для Staff-позиций в Дели в международных продуктовых компаниях обычно значительно выше среднего по рынку Индии. Указанный диапазон отражает уровень компенсации для опытных инженеров в топовых технологических компаниях региона.

Сопроводительное письмо

I am writing to express my strong interest in the Staff Analytics Engineer position at AlphaSense. With over 5 years of experience in analytics engineering and a deep proficiency in Python and SQL, I have a proven track record of building robust data pipelines and scalable Engineering Platforms. My expertise in Google Cloud Platform and AWS services like S3 and Lambda aligns perfectly with your R&D Analytical Data Lake initiatives.

In my previous roles, I have successfully bridged the gap between raw data ingestion and actionable business intelligence using Tableau. I am particularly drawn to AlphaSense's mission of removing uncertainty from decision-making through AI-driven insights. I am eager to bring my experience with event-driven systems and Kubernetes to your Global Product Analytics team and contribute to the continued innovation of your market intelligence platform.

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Откликнитесь в alphasense уже сейчас

Присоединяйтесь к AlphaSense, чтобы создавать передовые аналитические платформы на базе ИИ и определять будущее рыночной аналитики!

Описание вакансии

About AlphaSense:

The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content.

The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us!

About the Team:

The Global Product Analytics team comprises professionals with diverse expertise, including analytics, engineering, and data, striving for innovation, execution & delivery every day. The mission of the Product Analytics team is to empower decision-makers and the broader data communities within the R&D vertical and beyond through trusted data assets and scalable self-serve analytics. We are looking for professionals who are committed to learning and growing themselves while creatively delivering solutions to join our team.

The Role:

We are seeking a highly skilled and experienced Staff Analytics Engineer to join our Product Analytics team. This role requires

  • proficiency in Python to set up Engineering Platforms and configure robust data pipelines,
  • experience with the Google Cloud Platform (GCP) to run ETLs,
  • and hands-on experience in designing Tableau Workbooks.

The successful candidate will play a critical role in ingesting and transforming raw data into actionable insights to drive business decisions. If you're familiar with Scrum Agile methodologies and energetic, with a 'roll up your sleeves and do whatever it takes' attitude, we’d like to meet with you.

Requirements:

  • Bachelor's (or Master’s) degree  in Computer Science, Information Systems, or a closely related discipline
  • 5+ years of experience as an Analytics Engineer.
  • Overall solid programming skills, able to write modular, maintainable code in Python
  • Experience in creating data pipelines and transforming data using SQL in GCP
  • Experience in creating Tableau workbooks
  • Experience in working with AWS Services like S3, SNS, SQS, and AWS Lambda Function.
  • Experience in Kubernetes and CI/CD Process.
  • Experience in working with NoSQL DBs (e.g. MongoDB, DynamoDB)
  • Experience in working with event-driven systems.
  • Familiarity with Agile methodologies and product development processes
  • Excellent communication and collaboration skills

Responsibilities :

  • Develop R&D Analytical Data Lake for real-time data ingestion, storage, processing and analytics on BI tools
  • Develop and maintain data pipelines required for the extraction, transformation, cleaning, pre-processing, aggregation, and loading of data from a wide variety of data sources using Python and SQL
  • Develop Tableau dashboards by establishing connections with GCP and other tools

What we offer:

  • Playing a part in the story of a fast-growing company
  • Competitive compensation package
  • Exciting career opportunities and training
  • Very highly skilled colleagues
  • Lunch and recreational benefits
  • Occupational health care

AlphaSense is an equal-opportunity employer. We are committed to a work environment that supports, inspires, and respects all individuals. All employees share in the responsibility for fulfilling AlphaSense’s commitment to equal employment opportunity. AlphaSense does not discriminate against any employee or applicant on the basis of race, color, sex (including pregnancy), national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any other non-merit factor. This policy applies to every aspect of employment at AlphaSense, including recruitment, hiring, training, advancement, and termination.

In addition, it is the policy of AlphaSense to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations, and ordinances where a particular employee works.

Recruiting Scams and Fraud

We at AlphaSense have been made aware of fraudulent job postings and individuals impersonating AlphaSense recruiters. These scams may involve fake job offers, requests for sensitive personal information, or demands for payment. Please note:

  • AlphaSense never asks candidates to pay for job applications, equipment, or training.
  • All official communications will come from an @alpha-sense.com email address.
  • If you’re unsure about a job posting or recruiter, verify it on our Careers page.

If you believe you’ve been targeted by a scam or have any doubts regarding the authenticity of any job listing purportedly from or on behalf of AlphaSense please contact us. Your security and trust matter to us.

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Навыки

  • Python
  • SQL
  • Google Cloud Platform
  • Tableau
  • Amazon Web Services
  • Amazon S3
  • Amazon SNS
  • Amazon SQS
  • AWS Lambda
  • Kubernetes
  • CI/CD
  • MongoDB
  • DynamoDB
  • Agile
  • Scrum
  • ETL

Возможные вопросы на собеседовании

Проверка опыта работы с облачной инфраструктурой, указанной в требованиях.

Расскажите о вашем опыте проектирования ETL-процессов в GCP. Какие инструменты вы использовали для оркестрации?

Позиция требует навыков разработки платформ.

Как вы подходите к обеспечению модульности и поддерживаемости кода на Python в больших аналитических проектах?

В вакансии упоминаются SQS и SNS.

Опишите ваш опыт работы с событийно-ориентированными системами (event-driven systems). Как вы обрабатываете ошибки в таких пайплайнах?

Роль включает создание дашбордов.

С какими проблемами производительности в Tableau вы сталкивались при работе с большими объемами данных из GCP и как их решали?

Упоминается CI/CD и Kubernetes.

Какую роль играет Kubernetes в вашем текущем процессе развертывания аналитических инструментов?

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alphasense
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