Senior Data Engineer

4 weeks ago

Mumbai, India Grorapid labs Full time

Job 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 problem-solving and analytical skills.

- Strong communication and collaboration skills.

Position Overview:

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, high-performance database schemas and structures.

- Optimize and maintain existing database systems for efficiency and reliability.

2. 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.

3. Back-End Infrastructure:

- Build and manage the back-end infrastructure that supports data storage, retrieval, and processing.

- Ensure the security, integrity, and availability of data at all times.

4. Collaboration:

- Work closely with cross-functional teams to understand data needs and contribute to the development of data- driven solutions.

- Collaborate with front-end developers to integrate back- end data systems with user interfaces.

5. Performance Optimization:

- Identify and resolve performance bottlenecks in data processing and storage.

- Continuously monitor system performance and implement improvements as needed.

6. Documentation:

- Create and maintain comprehensive documentation for database schemas, ETL processes, and system architecture.

- Provide training and support to other team members on data-related technologies and best practices.

(ref:hirist.tech)

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