Summary

Job Context

---

Job Responsibilities

1. Data Ingestion: Design and implement data ingestion pipelines using Databricks and PySpark, with a focus on Autoloader for efficient data processing.
2. Nested JSON Handling: Develop and maintain processes for handling complex nested JSON files, ensuring data integrity and accessibility.
3. API Integration: Integrate and manage data from various APIs, ensuring seamless data flow and consistency.
4. Data Modeling: Create and optimize data models to support analytics and reporting needs.
5. Performance Optimization: Optimize data processing and storage solutions for performance and cost-efficiency.
6. Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver effective solutions.
7. Data Quality: Ensure the accuracy, integrity, and security of data throughout the data lifecycle.
8. Qualifications:
9. Technical Expertise: Proficiency in Databricks, PySpark, and SQL. Strong experience with Autoloader and handling nested JSON files.
10. API Experience: Demonstrated experience in integrating and managing data from various APIs.
11. Problem-Solving Skills: Strong analytical and problem-solving abilities.
12. Communication Skills: Excellent communication skills to collaborate with cross-functional teams.
13. Experience: Previous experience 3- 5 years in data engineering, data integration, and data modeling.
14. Education: A degree in Computer Science, Engineering, or a related field is preferred.
15. Preferred Qualifications:
16. Experience with cloud platforms such as AWS, Azure, or Google Cloud.
17. Familiarity with data warehousing concepts and tools.
18. Knowledge of data governance and security best practices.

---

Experience Requirements

• 2 - 4 years

Educational Requirements

• Bachelor/Honors

Skills

• iusto et

Age

• 25 - 35 Age

Additional Requirements

---

Compensation & Other Benefits

• - Tour , Medical , Holidays , Performance Bonus
• - Salary Review: Half Yearly

Work place

• Work At Office

Employment Status

• Full Time

Gender

• Male

Job Location

• India