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Data Engineer
1 month ago
Job Description :
The role described here is for a seasoned data engineer with 8 to 13 years of experience, showcasing proficiency across various aspects of data management and engineering.
Let's delve deeper into each requirement :
1. Data Engineering Experience :
- Candidates should possess a solid foundation in data engineering, indicating a substantial period (8 to 13 years) dedicated to working with data in various capacities.
- This tenure signifies a wealth of experience in handling diverse datasets and challenges that come with them.
2. Database Platform Expertise :
- The ideal candidate should be well-versed in both relational database management systems (RDBMS) like Oracle and MySQL, as well as NoSQL databases like MongoDB.
- This breadth of knowledge indicates versatility in handling different data models and structures.
3. Snowflake Proficiency :
- Hands-on experience with Snowflake, a popular cloud-based data warehousing platform, is essential.
- This indicates familiarity with modern data warehousing solutions and the ability to work effectively within such environments.
4. Data Pipeline Orchestration :
- Proficiency in orchestrating data pipelines is crucial.
- This involves designing, implementing, and maintaining data pipelines to ensure smooth and efficient data flow across various systems and processes.
5. Programming Language Skills :
- Candidates should be proficient in at least one programming language, preferably Python or Go.
- These languages are widely used in data engineering for tasks such as data manipulation, automation, and building scalable solutions.
6. Change Data Capture (CDC) and Kafka Knowledge :
- Experience in change data capture mechanisms and working knowledge of Kafka are valuable assets.
- This indicates familiarity with real-time data processing and streaming platforms, essential for handling dynamic and continuously evolving data sources.
7. Exposure to Data Warehousing and Data Lakes :
- Candidates should have exposure to data warehousing and data lake concepts.
- This includes understanding architectural principles, data modeling techniques, and best practices for managing large-scale data repositories.
- In summary, the ideal candidate for this role is an experienced data engineer with a strong background in database management, proficiency in Snowflake and data pipeline orchestration, programming skills in Python or Go, familiarity with CDC and Kafka, and exposure to data warehousing and data lake environments.
- This combination of skills equips them to tackle complex data engineering challenges and contribute effectively to data-driven initiatives within the organization.
(ref:hirist.tech)-
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