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- Aufgaben: Design and optimize data infrastructure while collaborating with teams to develop scalable solutions.
- Arbeitgeber: Join a dynamic company in Berlin focused on data-driven decision-making and innovative cloud technologies.
- Mitarbeitervorteile: Enjoy a hybrid work model, flexible hours, and opportunities for professional growth.
- Warum dieser Job: Be part of a collaborative culture that values data integrity and empowers impactful decision-making.
- Gewünschte Qualifikationen: 3+ years in data engineering with experience in cloud platforms and data modeling.
- Andere Informationen: Work with cutting-edge tools like Google Cloud and contribute to exciting data projects.
Das voraussichtliche Gehalt liegt zwischen 43200 - 72000 € pro Jahr.
About the Role:
We are looking for a Data Engineer to design, build, and optimize our data infrastructure. In this role, you will work with both technical and non-technical teams to develop scalable data solutions. You will help enable data-driven decision-making across the company by ensuring data quality, efficient data processing, and cost-effective cloud architectures.
You will report to the Team Lead Sales Data & BI. This role is hybrid and located in Berlin.
What You’ll Do:
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Data Architecture & Pipelines: Design, develop, and maintain scalable ETL/ELT pipelines to support analytical and operational data needs.
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Data Modeling: Structure and improve data models for various data products to ensure performance and usability.
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Business & Technical Collaboration: Translate business requirements into technical solutions and collaborate with teams to align on data strategies.
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Performance & Cost Optimization: Implement best practices for query optimization, cloud cost management, and efficient data storage.
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Data Quality & Governance: Develop and implement monitoring, testing, and validation frameworks to ensure data integrity and consistency.
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Workflow Automation: Use orchestration tools to automate and manage data workflows efficiently.
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Stakeholder Management: Work closely with analysts, data scientists, and business teams to provide reliable and well-structured data.
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Cloud & Tooling: Leverage modern cloud technologies and data engineering best practices to enhance our data platform.
Who You Are:
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Experience: 3+ years in a data engineering role, working with large datasets and cloud-based data platforms.
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Data Architecture & Modeling: Strong understanding of data modeling principles and experience designing scalable data solutions.
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Cloud & Big Data Technologies: Hands-on experience with Google Cloud (GCP) or comparable platforms (AWS, Azure), including BigQuery / Google Cloud Storage.
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ETL/ELT & Orchestration: Experience with Dataform / dbt, Apache Airflow / Google Cloud Composer, or similar tools.
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Streaming & Processing: Knowledge of Kafka and Spark (Serverless) is a plus.
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CI/CD & Automation: Familiarity with CI/CD pipelines for data deployment and workflow automation.
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Visualization & Reporting: Experience with BI tools such as Looker, Tableau, or Power BI is a plus.
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Data Engineer (d/f/m) Arbeitgeber: Adevinta 2021
Kontaktperson:
Adevinta 2021 HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Data Engineer (d/f/m)
✨Tip Number 1
Familiarize yourself with the specific cloud technologies mentioned in the job description, especially Google Cloud Platform (GCP) and BigQuery. Having hands-on experience with these tools will give you a significant edge during the interview process.
✨Tip Number 2
Brush up on your ETL/ELT skills, particularly with tools like Dataform/dbt and Apache Airflow. Being able to discuss your past projects involving these tools will demonstrate your practical knowledge and problem-solving abilities.
✨Tip Number 3
Prepare to showcase your experience in data modeling and architecture. Think of examples where you've designed scalable data solutions and be ready to explain your thought process and the impact of your work.
✨Tip Number 4
Highlight your collaboration skills by preparing examples of how you've worked with both technical and non-technical teams. This role emphasizes business and technical collaboration, so showing that you can bridge the gap will be crucial.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Data Engineer (d/f/m)
Tipps für deine Bewerbung 🫡
Understand the Role: Make sure to thoroughly read the job description and understand the key responsibilities and requirements. Tailor your application to highlight your relevant experience in data engineering, cloud technologies, and ETL/ELT processes.
Highlight Relevant Experience: In your CV and cover letter, emphasize your 3+ years of experience in data engineering, particularly with large datasets and cloud platforms like Google Cloud or AWS. Mention specific projects where you designed scalable data solutions or optimized data pipelines.
Showcase Technical Skills: Clearly list your technical skills related to data architecture, modeling, and tools such as Dataform, Apache Airflow, and BI tools. Provide examples of how you've used these technologies to solve problems or improve processes in previous roles.
Craft a Compelling Cover Letter: Write a cover letter that not only summarizes your qualifications but also expresses your enthusiasm for the role and the company. Discuss how your background aligns with their goals for data-driven decision-making and collaboration across teams.
Wie du dich auf ein Vorstellungsgespräch bei Adevinta 2021 vorbereitest
✨Showcase Your Technical Skills
Be prepared to discuss your experience with data architecture, ETL/ELT processes, and cloud platforms like Google Cloud. Highlight specific projects where you designed scalable data solutions or optimized data pipelines.
✨Demonstrate Collaboration Abilities
Since the role involves working with both technical and non-technical teams, share examples of how you've successfully translated business requirements into technical solutions. Emphasize your communication skills and teamwork.
✨Discuss Data Quality Practices
Talk about your approach to ensuring data integrity and consistency. Mention any frameworks or tools you've implemented for monitoring and validation, as this is crucial for the role.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Be ready to explain how you would handle performance optimization or cost management in a cloud environment.
