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- Aufgaben: Design and optimize data pipelines and infrastructure for large data volumes.
- Arbeitgeber: Join a dynamic team focused on innovative data solutions.
- Mitarbeitervorteile: Enjoy flexible work options and opportunities for professional growth.
- Warum dieser Job: Be at the forefront of data engineering, collaborating with diverse teams and technologies.
- Gewünschte Qualifikationen: Bachelor's in Computer Science or related field; strong skills in Python, SQL, and cloud platforms.
- Andere Informationen: Experience in finance is a plus, but not required.
Das voraussichtliche Gehalt liegt zwischen 48000 - 84000 € pro Jahr.
Your mission
We are looking for an experienced Senior Data Engineer to join our team. In this role, you will be responsible for developing and optimizing our data pipelines and infrastructure. You will continuously improve the quality of our data architecture by leveraging your technical expertise and attention to detail. A deep understanding of SQL, Python , and Big Data technologies (e.g., BigQuery, Hadoop, Spark, Kafka) is required. Experience with cloud data platforms such as GCP or AWS, as well as knowledge of ETL processes and database management systems , is a plus. Your ability to work independently, demonstrate team spirit, and stay up-to-date in a dynamic environment is essential.
Responsibilities
- Designing and implementing data pipelines: Designing and implementing efficient and scalable data pipelines that collect, process, and store large volumes of structured and unstructured data from various sources.
- Developing and maintaining data infrastructure: Developing and maintaining data infrastructure, such as data warehouses, data lakes, and databases, to support data storage, processing, and analysis.
- Ensuring data quality and integrity: Ensuring data quality and integrity by implementing data validation and cleansing processes, monitoring data accuracy and completeness, and resolving data quality issues.
- Collaborating with cross-functional teams: Collaborating with cross-functional teams, such as data scientists, analysts, and product managers, to understand their data needs and provide data solutions that meet their requirements.
- Optimizing data performance: Optimizing data performance by tuning database queries, designing data models, and implementing data indexing and partitioning techniques.
- Implementing data security and privacy measures: Implementing data security and privacy measures to protect sensitive data, such as encrypting data at rest and in transit, and managing user access and authentication.
- Keeping up with new technologies: Keeping up with new technologies and industry trends in data engineering, such as cloud computing, big data, and machine learning, to identify opportunities for innovation and improvement.
Functional Fit
- Bachelor’s degree in Computer Science, Engineering, or a related field
- Experience with cloud computing (AWS, GCP)
- Proficient in Python and SQL
- Experience with containers (Docker, Kubernetes)
- Experience in building and expanding data warehouse, data lake and transformation pipelines.
- Experience in the financial sector is a plus, but not a must.
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Senior Data Engineer (m/f/d) Arbeitgeber: Smartbroker
Kontaktperson:
Smartbroker HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Senior Data Engineer (m/f/d)
✨Tip Number 1
Make sure to showcase your experience with cloud platforms like AWS and GCP. Highlight specific projects where you've implemented data solutions using these technologies, as this will demonstrate your hands-on expertise.
✨Tip Number 2
Familiarize yourself with the latest trends in big data technologies such as Hadoop, Spark, and Kafka. Being able to discuss recent advancements or your personal experiences with these tools can set you apart during discussions.
✨Tip Number 3
Prepare to discuss your approach to ensuring data quality and integrity. Be ready to share examples of how you've implemented data validation processes or resolved data quality issues in previous roles.
✨Tip Number 4
Emphasize your ability to work collaboratively with cross-functional teams. Share instances where you've successfully partnered with data scientists or product managers to deliver effective data solutions that meet their needs.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Senior Data Engineer (m/f/d)
Tipps für deine Bewerbung 🫡
Highlight Relevant Experience: Make sure to emphasize your experience with SQL, Python, and Big Data technologies in your CV and cover letter. Provide specific examples of projects where you designed and implemented data pipelines or optimized data performance.
Showcase Technical Skills: Clearly list your technical skills related to cloud platforms like GCP or AWS, as well as your familiarity with ETL processes and database management systems. This will demonstrate your fit for the role.
Tailor Your Application: Customize your application materials to reflect the responsibilities mentioned in the job description. For instance, discuss your experience in collaborating with cross-functional teams and how you ensured data quality and integrity in past roles.
Express Continuous Learning: Mention any recent courses, certifications, or self-study efforts related to new technologies in data engineering. This shows your commitment to staying up-to-date in a dynamic environment.
Wie du dich auf ein Vorstellungsgespräch bei Smartbroker vorbereitest
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, Python, and Big Data technologies in detail. Highlight specific projects where you designed and implemented data pipelines or optimized data performance.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your ability to troubleshoot data quality issues or optimize data infrastructure. Use examples from your past work to illustrate how you approached and resolved these challenges.
✨Emphasize Collaboration
Since the role involves working with cross-functional teams, be ready to share experiences where you collaborated with data scientists, analysts, or product managers. Discuss how you understood their data needs and provided effective solutions.
✨Stay Updated on Industry Trends
Show your enthusiasm for continuous learning by discussing recent trends in data engineering, cloud computing, or machine learning. Mention any relevant courses, certifications, or personal projects that demonstrate your commitment to staying current.
