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Senior Backend Data Engineer
1 week ago
Job Description :
- Bachelor's or advanced degree in Computer Science, Information Technology, or related field.
- Proven experience as a Back-End Data Engineer or similar role.
- Proficiency in database design and management (e.g., SQL, NoSQL).
- Strong programming skills in languages such as Python, Java, or Scala.
- Experience with ETL tools and data integration processes.
- Knowledge of cloud platforms (e.g., AWS, Azure, GCP) and their data services.
- Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus.
- Excellent problemsolving and analytical skills.
- Strong communication and collaboration skills.
As a Back-End Data Engineer, you will play a crucial role in designing, implementing, and maintaining the back- end infrastructure that supports our data ecosystem.
You will work closely with cross-functional teams, including data scientists, analysts, and software engineers, to ensure efficient data processing, storage, and retrieval.
The ideal candidate is not only technically proficient but also possesses a deep understanding of data modeling, database architecture, and data :Database Design and Maintenance :
- Design and implement scalable, highperformance database schemas and structures.
- Optimize and maintain existing database systems for efficiency and reliability.
Data Pipeline Development :
- Develop and maintain robust ETL (Extract, Transform, Load) processes for efficient data movement and transformation.
- Collaborate with data scientists and analysts to understand data requirements and implement solutions accordingly.
Back-End Infrastructure :
- Build and manage the backend infrastructure that supports data storage, retrieval, and processing.
- Ensure the security, integrity, and availability of data at all times.
Collaboration :
- Work closely with crossfunctional teams to understand data needs and contribute to the development of datadriven solutions.
- Collaborate with frontend developers to integrate back end data systems with user interfaces.
Performance Optimization :
- Identify and resolve performance bottlenecks in data processing and storage.
- Continuously monitor system performance and implement improvements as needed.
Documentation :
- Create and maintain comprehensive documentation for database schemas, ETL processes, and system architecture.
- Provide training and support to other team members on datarelated technologies and best practices. )
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