1. Bachelor degree

2. Must have completed one of the following certifications:

• Data Engineering certification

• Database Administrator certification (Oracle or Sql server)

3. Must have 8+ yrs. of Experience in IT Industry with 3+ yrs. experience in software e development and administering database.

4. Must have 3+ yrs. experience as Data engineer.

5. Technical expertise in data models, data mining, and segmentation techniques 6. Experience in database design

7. Experience in numerical and analytical skills

8. Experience in Data analysis, validation, and Data cleansing.

9. Experience writing reports, business correspondence and procedure documentation.

10. Experience in Python programming language, Pandas, Numpy, etc.

11. Experience in Writing, deploying, testing, and maintaining a data pipeline (ELT/ETL) to build architecture and integrate data systems.

12. Experience in Handling data transformations to cleanse irregular and unstructured data before that data has moved to the target systems

13. Experience in Improving the existing data architecture or build a new system emphasizing data security, data quality and timeliness, scalability, and extensibility.

14. Experience in deploying secure and well-tested pipelines that meet privacy and compliance requirements.

15. Experience in Investigating data discrepancies between multiple systems

16. Experience in creating long-term view of data system design architecture and use cases of data products supporting analytics, big data, and AI

. 17. Experience in comparing, reviewing and evaluating various alternative solutions considering both technical and business requirements/parameters and at the same time ensuring that the solution is viable as per defined cost and service requirements.

18. Experience in mentoring and guiding the team on tools, technology, and data engineering design patterns.

19. Experience in Database programming and optimization using multiple flavors of relational and non-relational data with various source data types.

20. Experience in data modeling, data transformation (DBT), and building data warehouses, data lake platforms on premise systems and cloud computing platforms.

21. Experience in solving problems and finding solutions around the distributed system, storage, transactions and query processing

22. Basic knowledge of cloud environments including Kubernetes, Docker, and DevOps

23. Experience in data visualization and dashboarding tools like Google Data Studio, PowerBI etc.

24. Installing, validating, testing, and packaging Hadoop products on Linux platforms