Google Cloud Platform Data Engineer (AI Experience)

Required - minimum 7 years of proven hands-on experience with Google Cloud Platform data services.

Preferred - Google Cloud Platform Google Cloud Professional Data Engineer Certification.

Required Strong understanding of distributed systems and data engineering best practices.

Required Excellent communication and documentation skills.

Required Ability to work independently and collaboratively in a fast-paced environment.

Required experience in Agile methodology with preferred experience in SAFe methodology

Required good communication and collaborative skills

Required experience working in onshore/offshore support model collaborating work with offshore teams.

Preferred experience working with GitHub, RTC, automation tools.

Required - minimum 3 years of proven hands-on experience in the following:

•           Design and implement robust data pipelines using Google Cloud Platform (Google Cloud Platform) services such as BigQuery, Cloud Storage, and Pub/Sub.

•           Develop and manage workflows using Cloud Composer (Apache Airflow) for efficient scheduling and orchestration.

•           Write clean, efficient, and scalable code in Python, leveraging advanced programming techniques.

•           Craft complex SQL queries in BigQuery, including window functions, CTEs, and performance tuning strategies.

•           Build and maintain real-time data processing systems using Apache Kafka.

•           Model and manage NoSQL databases, particularly MongoDB, with a focus on scalable schema design.

•           Utilize Shell scripting and perform Linux system administration tasks to support data infrastructure.

•           Conduct data profiling and implement validation techniques to ensure data quality and integrity.

•           Develop and maintain API integration scripts for seamless service automation and data exchange.

•           Troubleshoot and resolve data-related issues with strong analytical and problem-solving skills.

•           Create and maintain data flow diagrams to clearly communicate architecture and pipeline logic to stakeholders.