出海雷达

数据工程师(瑞典)

Data Engineer (Sweden)

开发工程未标注地域
公司AIDA Recruitment
薪资未公开
工作地点Latvia
地域资格未标注地域
时区要求日间重叠约 3 小时,需偶尔早起或晚睡
用工类型Contractor
发布时间6 天前
数据来源Himalayas
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关于本页中文:职位描述由本机离线模型翻译,属机器翻译,供快速判断用;正式沟通与投递请以英文原文为准。官方翻译通道恢复后会自动重译升级。

关于角色 我们的客户,我们正在寻找一个经验丰富的数据工程师加入瑞典最终客户的电信项目。这是一个远程 B2B 合同职位,专注于建立和维护可扩展的数据管道,与大型数据集合作,并支持云计算环境中的可靠数据处理。你将在国际环境中与工程团队协作时使用配套工具,分布式数据处理技术以及 CI/CD 实践工作。该职位适用于基于欧盟的国家的 EU 候选人。可能需要偶尔前往客户的办公室瑞典。关键责任 ·设计,构建和维护复杂的 ETL 和数据处理管道。· 在分布式数据环境中与大型数据集进行合作。·使用 Spark 和 Python 开发数据处理解决方案。·利用工具如 Airflow 建立和维护工作流配套。·开发和改进基于云的数据解决方案,包括 GCP 等环境。·确保数据管道可靠,可维护和可扩展性。·解决数据处理问题并调查数据输出故障。·优化现有数据工作流和处理性能。·通过 Jenkins 和 Git 等工具为 CI/CD 进程做出贡献。· 应用软件工程原则到数据工程解决方案。· 写清洁,可维护和结构化的代码。· 参加代码审查和技术讨论。· 与其他工程师和技术利益相关者合作。·支持不断改善工程实践和交付流程。· 在团队中贡献技术文档和知识共享。基本要求。· 数据工程方面的强有经验。· 使用空气流等编排工具的工作实践经验。•与大型数据集工作经验。· 云平台,特别是 GCP 或类似环境的实践经验。· Apache Spark 强大的编程技能。· Scala 编程经验强大。· Python 编程经历强大。• 在 CI/CD 工具和工作流程中体验强大,包括 Jenkins 和 Git. ·软件工程原则和开发实践的强有力的理解。· 分析能力强大,解决问题能力强大。

查看英文原文

About the Role
For our client, we are looking for an experienced Data Engineer to join a telecommunications project for an end customer in Sweden.
This is a remote B2B contract role focused on building and maintaining scalable data pipelines, working with large datasets, and supporting reliable data processing across cloud-based environments.
You will work with orchestration tools, distributed data-processing technologies, and CI/CD practices while collaborating with engineering teams across an international environment.
The role is suitable for candidates based in the EU with EU nationality. Occasional travel to the client's office in Sweden may be required.
Key Responsibilities

  • Design, build, and maintain complex ETL and data-processing pipelines.
  • Work with large-scale datasets across distributed data environments.
  • Develop data-processing solutions using Spark with Scala and Python.
  • Build and maintain workflow orchestration using tools such as Airflow.
  • Develop and improve cloud-based data solutions, including environments such as GCP.
  • Ensure data pipelines are reliable, maintainable, and scalable.
  • Troubleshoot data-processing issues and investigate pipeline failures.
  • Optimise existing data workflows and processing performance.
  • Contribute to CI/CD processes using tools such as Jenkins and Git.
  • Apply software engineering principles to data-engineering solutions.
  • Write clean, maintainable, and well-structured code.
  • Participate in code reviews and technical discussions.
  • Collaborate with other engineers and technical stakeholders.
  • Support continuous improvement of engineering practices and delivery processes.
  • Contribute to technical documentation and knowledge sharing across the team.

Essential Requirements

  • Strong professional experience in data engineering.
  • Hands-on experience working with orchestration tools such as Airflow.
  • Experience working with large datasets.
  • Strong experience building complex ETL pipelines.
  • Practical experience with cloud platforms, particularly GCP or similar environments.
  • Strong programming skills with Apache Spark.
  • Strong Scala programming experience.
  • Strong Python programming experience.
  • Experience with CI/CD tools and workflows, including Jenkins and Git.
  • Strong understanding of software engineering principles and development practices.
  • Strong analytical and problem-solving skills.
  • Good communication skills and ability to collaborate effectively in an international engineering environment.
  • EU nationality and ability to work from within the EU.
  • Willingness to travel occasionally to Sweden when required.

Preferred Requirements

  • Experience working on large-scale distributed data platforms.
  • Experience optimising Spark-based workloads and data-processing performance.
  • Familiarity with cloud-native data services and managed data-processing tools.
  • Experience working in telecommunications or similarly data-intensive environments.
  • Knowledge of data-quality, monitoring, and observability practices.
  • Experience with automated testing for data pipelines and transformation logic.
  • Previous experience working in distributed international teams.

What We Value
We value engineers who are technically strong, pragmatic, and comfortable taking ownership of complex data-engineering challenges. Reliability, maintainability, and scalability should guide your approach to designing and improving data solutions.
Clear communication and collaboration are equally important. You should be comfortable working independently in a remote environment while contributing actively to technical discussions and team delivery.
What You Can Expect

  • A technically challenging data-engineering project in the telecommunications sector.
  • Hands-on work with Spark, Scala, Python, orchestration tools, and cloud-based data environments.
  • Exposure to large datasets and complex ETL pipelines.
  • Collaboration with an international engineering team.
  • A remote-first working model.
  • Occasional business travel to Sweden.
  • Opportunity to contribute to technical decisions and engineering improvements.

What We Offer

  • Project / Industry: Telecommunications project for an end customer in Sweden.
  • Location: Remote within the EU, with occasional visits to Sweden.
  • Contract Type: B2B contractor.
  • Compensation: €40–45/hour.
  • Start Date: Preferred start between the end of September and October.
  • Work Model: Remote.
  • Contract Duration: 6 months, with the possibility of extension.

Recruitment Process

  • CV Screening: Applications are reviewed within 24 hours.
  • Pre-Screening Interview: A brief Q&A session, automated or with a recruiter, designed to learn more about your experience related to the position.
  • Automated Session (Recommended) – You can complete the session independently at a convenient time. The structured questions and follow-ups are designed to capture detailed, role-relevant experience and can support faster hiring-manager feedback.
  • Session with a Recruiter – You can complete the same pre-screening with a recruiter. The discussion may be less detailed and feedback may take slightly longer.
  • Shortlisting: Qualified candidates are presented to the hiring manager for review.
  • Formal Interviews: Discussions with the hiring manager or project team, with feedback typically provided within 1–2 weeks.
  • Offer and Onboarding: Successful candidates receive a formal offer and begin the onboarding process.

Information about the processing of your personal data is provided in our Privacy Policy, which is available online at Privacy Policy.
Originally posted on Himalayas

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