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SeniorГибридПолная занятость

Senior Data Engineer

Оценка ИИ

Отличная вакансия с современным стеком (AWS, dbt, Snowflake), прозрачной культурой и сильным социальным пакетом (обучение, бонусы, гибкость). Компания работает с огромными масштабами данных, что дает отличные возможности для профессионального роста.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует глубоких знаний AWS, Python и Spark, а также опыта работы с высоконагруженными системами (тысячи событий в секунду). Ожидается владение современным стеком (dbt, Airflow) и понимание принципов Software Engineering.

Анализ зарплаты

Медиана27 000 PLN
Рынок20 000 PLN – 35 000 PLN
Оценка ИИ

Зарплата в объявлении не указана, но для Senior Data Engineer в Польше (Вроцлав) рыночный диапазон составляет 22,000–32,000 PLN в месяц (gross). Предложение Auctane, вероятно, находится в этом диапазоне, учитывая ежегодный пересмотр и бюджет на обучение.

Сопроводительное письмо

I am writing to express my strong interest in the Senior Data Engineer position at Auctane. With over five years of experience in building robust data pipelines and a deep expertise in Python, SQL, and the AWS ecosystem, I am confident in my ability to contribute significantly to your Data Products team. My background in designing scalable data lake architectures and working with processing frameworks like Spark and Athena aligns perfectly with Auctane's mission to handle massive datasets at scale.

Throughout my career, I have been a staunch advocate for engineering excellence, implementing CI/CD patterns and ensuring data observability. I am particularly drawn to Auctane's flat engineering culture and the opportunity to work on greenfield projects using state-of-the-art tools like dbt and Airflow. I am eager to bring my technical skills and passion for data-driven decision-making to help Auctane continue its impressive growth and deliver exceptional value to its global customer base.

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Присоединяйтесь к Auctane, чтобы строить современные дата-платформы и влиять на глобальную логистику!

Описание вакансии

About us

At Auctane, we are united by a passion to help businesses deliver — whatever their size, wherever they are, and however they operate. We make it possible for businesses to meet the ever-changing requirements of their industry and customer expectations. Auctane products enable hundreds of thousands of businesses to annually mail and ship billions of items — over $200 billion worth — to recipients around the globe.

The Auctane family of mailing and shipping software products includes ShipStation, Stamps.com, ShipStation API, Metapack, GlobalPost, and Packlink. Our partners include Amazon, UPS, USPS, eBay, BigCommerce, Shopify, WooCommerce, and Walmart.

Our values

![](https://postimg.cc/N5Q8NR10)Win as One. Delight Customers. Deliver Great Outcomes.

About the role

This is a hands-on role for a Senior Data Engineer sitting within the Data Products team. In this role, you will have an enormous impact on the design, implementation, and maintenance of existing and greenfield customer-facing data products. Data is key to Auctane’s strategy. We work at a scale pace and with the latest architecture patterns and tech. We process thousands of events per second, and our massive dataset keeps growing at a staggering pace. We keep improving our data platform and data engineering stack to accommodate growth, enable novel solutions, and provide the best service to our customers. We have a flat and open engineering culture where data & evidence beat opinion and hierarchy, backed by honest discussions. We passionately believe in forming autonomous, cross-functional teams who are empowered to deliver our ambitious strategy. Energy and passion for our business and customers are a part of the Auctane culture – and we love working with like-minded people.

What will you be doing?

  • Contribute to the design, build, and operational management of our data pipelines and analytics solution on top of proven AWS data technologies like S3, Athena, Lambda, and Kinesis.
  • Collaborate with the Product Owner and other stakeholders to implement the Data Products strategy.
  • Develop frameworks and solutions that enable us to acquire, process, monitor and extract value from our massive dataset.
  • Drive the design and architecture of Auctane’s data product.
  • Contribute directly to the implementation and operations of our systems.
  • Be an advocate of data quality and observability principles and use state-of-the-art technologies like Airflow, dbt, and Spark to process data and get our datasets just right.
  • Foster engineering excellence by delivering highly reliable software and data pipelines using Software Engineering best practices like automation, version control, continuous integration/continuous delivery, testing, security, etc.

What are we looking for?

  • At least 5 years of proven experience in data engineering roles
  • A strong Data Engineering background in a data warehouse or data lake architecture
  • Experience working in AWS/GCP cloud infrastructure.
  • Experience developing and supporting robust, automated, and reliable data pipelines in Python and SQL.
  • Mastered Python and SQL skills.
  • Experience with data processing frameworks like Spark, Athena, or Pandas.
  • Knowledge of Data Orchestration solutions, preferably Airflow.
  • Knowledge of relational database design as well as Snowflake/Redshift or similar

What will make you stand out?

  • Production experience working with very large datasets.
  • Experience with AWS and big data cloud technologies like EMR, Athena, Glue, and EC2.
  • Direct experience with Infrastructure as Code tools (e.g., Terraform, CloudFormation)
  • Knowledge and direct experience in using business intelligence and analytics tools (Tableau, Looker, Power BI, etc.)
  • A desire to constantly challenge the norm Proven track record of promoting and maintaining high engineering standards.
  • Fast learner with a keen interest in evaluating and adopting new technologies: Apache Iceberg, Dagster, DBT, GreatExpectations, Prefect, Snowflake, etc.
  • Understanding of core ML concepts like supervised and unsupervised learning, overfitting, and cross-validation as well as LLM concepts like fine-tuning, etc.

Tech stack

Python SQL Amazon Web Services C# .NET

What do we offer?

  • 🗓️ Annual Salary Review:We are reviewing the salaries of all our teams annually in order to evaluate an increase according to individual performance and the business results.
  • 📦 99% discount on your personal shipment orders via Packlink.pro
  • 💙 Up to 500PLN/year to match your NGO donations! We are happy to support your initiatives by duplicating the amount donated.
  • 😊 Volunteer day.You can take 1 day off per year in order to participate in volunteering activities! We will love to see some pictures in our slack!
  • Referral Fee🔗 We need your support in hiring top-class talent! We offer a referral bonus of 4-20k, depending on the complexity of the role and the hiring process.
  • 👩‍⚕️We have an Employee Assistance Programwith psychological assistance free of charge.
  • ⚖️ Great work-life balance We offer a flexible work schedule and will do our best to adapt to your personal situation. Working in a fast-paced environment can be intense, but that doesn’t mean you shouldn’t enjoy your free time!
  • 💜 An inclusive and upbeat work environmentLeave your suit behind... we’re a t-shirt and converse kind of place! More importantly, our company culture promotes diversity and inclusion. The personality and opinions of each of our team members are important and valid, and we aim to offer all employees a safe environment where they can be themselves and thrive.
  • 🌍 Across-cultural atmosphereWe are a truly international team of 20 nationalities that speak 10 languages. Our company language is English and all internal communication and company-wide meetings are in English.
  • 🏟️ Company events Work hard, play hard! We do our best every day, even at our regular team-building events.
  • 📺 Internal and external training, free access to online training platforms such as Linkedin Learning
  • 🏠 Possibility to work in a home-officeusing equipment provided by AUCTANE, or in our office prepared in accordance with all safety requirements.
  • 📙 Personal Training Budget.Up to 7000 PLN/year training budget (certifications, conferences attendance, etc.) to invest in your professional development. We want to help you improve your technical skills, feel involved in the product community, and develop your soft skills to lead teams and manage other stakeholders.
  • 🌅 Up to 30 days of vacation per year (additional days are granted along with seniority at AUCTANE).
  • 🗺️ Languages classesevery week. Thirsty for knowledge? Learn a new language by joining our free English/Spanish/German classes. You can connect and enjoy taking up a new language or improving your current skills with one of our great instructors.
  • 🏥 Free private medical insurance.
  • 📄 Attractive life insurance.
  • 🏐  Co-financing forsports and recreational activities
  • 🏐Gym membership co-financing
  • 🏢 Nice Office in Zielona Gora and Wroclaw (free drinks, snacks…)
  • Do you want to know a little bit more about the team? Please, don’t hesitate to reach out to Amazing Auctane-PLand our Instagram

#LI-HYBRID

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Навыки

  • Python
  • SQL
  • AWS
  • C++
  • .NET
  • Apache Spark
  • AWS Athena
  • AWS Lambda
  • AWS Kinesis
  • Amazon S3
  • Airflow
  • dbt
  • Snowflake
  • Amazon Redshift
  • Terraform
  • Pandas
  • Apache Iceberg
  • CI/CD

Возможные вопросы на собеседовании

Проверка опыта работы с масштабируемыми системами, упомянутыми в описании.

Расскажите о вашем опыте проектирования дата-пайплайнов, обрабатывающих тысячи событий в секунду. Какие инструменты AWS вы использовали для обеспечения отказоустойчивости?

Вакансия предполагает использование dbt и Airflow для обеспечения качества данных.

Как вы организуете процесс тестирования и обеспечения качества данных (Data Quality) в среде dbt и Airflow?

В стеке указаны Spark и Athena. Важно понять, когда кандидат выбирает тот или иной инструмент.

В каких сценариях вы предпочтете использовать Apache Spark вместо AWS Athena для обработки больших объемов данных?

Упоминается важность инженерной культуры и CI/CD.

Опишите ваш подход к реализации CI/CD для инфраструктуры данных. Как вы используете Terraform или другие IaC инструменты?

В 'Stand out' секции указаны ML и LLM.

Был ли у вас опыт подготовки данных для моделей машинного обучения или работы с векторными базами данных для LLM?

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