Data Engineer

• Build, maintain, and optimize data pipelines and storage solutions to ensure data quality, accessibility, and performance for automation testing and AI applications.
• Develop, implement, and maintain Python-based solutions for ETL processes, data transformation, and system integration.
• Integrate data engineering workflows with AI and machine learning applications, ensuring compatibility and scalability.
• Design and implement REST APIs and WebSocket connections for real-time data transfer and integration.
• Collaborate closely with AI and R&D teams to support new AI features, ensuring seamless integration with data systems.
• Work on distributed systems to ensure scalability and reliability for high-volume data processing tasks.
• Implement and optimize data solutions for structured and unstructured data, including SQL and NoSQL databases.
• Participate in system design and architecture discussions to create high-performance, scalable, and maintainable systems.

Data Engineer

Skills

1.Python

2.Problem Solving and Programming

3.Data Engineering

4.GenerativeAI

5.REST APIs

6.WebSockets

7.UI and Integration

8.Data Pipelines

9.SQL & NoSQL Databases

10.Distributed Systems

11.High & Low-level System Design

12.Data Warehouses and Lakes

13.AIOps

14.RPA

What We are Looking For

• Hands-on Python Expertise

  : Ability to write efficient, maintainable, and scalable code daily.

• Implementation-Oriented

  : A focus on delivering working code and solutions, not just theoretical designs.

• Team Collaboration

  : A proactive team player who thrives in a collaborative environment.

• Data Expertise

  : Solid knowledge of data transformation, storage, and real-time data integration techniques.
• This role is a fantastic opportunity for individuals who enjoy working closely with data, building practical solutions, and pushing the boundaries of automation testing with AI.