Data Engineer

1. Design and implement scalable data architectures and data models to
support data collection, transformation, and storage.
2. Develop and maintain data pipelines and Extract, Transform, Load
processes to ensure efficient data flow.
3. Optimize database performance, storage, and retrieval processes.
4. Integrate data from various sources, including databases, APIs, and
external datasets.
5. Ensure data quality, integrity, and consistency through data
validation and cleansing processes.
6. Manage data warehouses and data lakes to support analytics and
reporting needs.
7. Develop and maintain data processing scripts and workflows using
programming languages such as Python, SQL, and Java.
8. Implement data transformation logic to prepare data for analysis and
reporting.
9. Ensure timely and efficient processing of large-scale data sets.
10. Work closely with data scientists, analysts, and business
stakeholders to understand data requirements and provide technical
solutions.
11. Collaborate with software engineers and IT teams to ensure seamless
integration of data systems.
12. Communicate effectively with technical and non-technical
stakeholders to explain data engineering concepts and solutions.
13. Implement data security measures to protect sensitive and
confidential information.
14. Ensure compliance with relevant data protection regulations and
industry standards.
15. Monitor and maintain data access controls and permissions.
16. Monitor the performance of data systems and infrastructure to
identify and resolve issues.
17. Optimize data pipelines and database queries for maximum efficiency
and speed.
18. Implement best practices for data engineering and continuously
improve processes.
19. Maintain detailed documentation of data architecture, processes, and
workflows.
20. Prepare and present reports on data engineering activities and
system performance.
21. Use data-driven insights to make informed decisions and drive
continuous improvement. 3 - 8 years

Skills & Competencies :

1.