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2 дня назад

Senior Data Engineer

Формат работы
remote (Global)
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
Serbia, Poland, Georgia
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Senior Data Engineer (Data): Designing, implementing, and maintaining scalable data pipelines and storage solutions with an accent on AWS data services. Focus on optimizing data storage, processing, and retrieval, ensuring data integrity and compliance.

Location: Remote. Possibility for working in Warsaw office.

Company

hirify.global is a rapidly scaling technology company specializing in working with and investing in prominent start-ups and brands in building and scaling their digital products.

What you will do

  • Design, develop, and maintain scalable ETL/ELT pipelines and data workflows.
  • Optimize data storage, processing, and retrieval using cloud-based technologies, with a strong focus on AWS.
  • Work with structured and unstructured data across various databases and data lakes.
  • Ensure data integrity, security, and compliance with industry standards.
  • Collaborate with cross-functional teams to define data requirements and support analytics and machine learning initiatives.
  • Monitor and improve data infrastructure performance, ensuring reliability and scalability.

Requirements

  • 5+ years of experience in data engineering or a related field.
  • Strong expertise in AWS data services (e.g., Redshift, Glue, Athena, S3, Lambda, Kinesis, etc.).
  • Experience with big data technologies such as Apache Spark, Apache Airflow, or similar tools.
  • Strong knowledge of SQL and data modeling, schema design.
  • Strong hands-on experience in Python
  • Knowledge of CI/CD pipelines and infrastructure-as-code (Terraform, CloudFormation) is a plus.
  • Fluent English (B2) with both written and spoken skills used for clear and active communication with native speakers

Nice to have

  • Experience with real-time data streaming and event-driven architectures.
  • Exposure to machine learning workflows and MLOps practices.
  • Knowledge of security and compliance standards in data engineering.
  • Experience with GCP or Azure is a plus (BigQuery, Databricks, Azure Data Factory, etc.)

Culture & Benefits

  • Vacation leave of 20 working days
  • Paid Medical insurance
  • 4 sick days per year
  • Sport compensation
  • Career and professional growth
  • Access to senior engineers for help and mentorship

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