Design and implement robust data pipelines using Google Cloud Platform (GCP) 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
Qualifications
Required: Minimum 7 years of proven hands-on experience with GCP data services
Required: Minimum 3 years of proven hands-on experience with the core technical responsibilities listed above (data pipelines, Cloud Composer, Python, BigQuery SQL, Apache Kafka, MongoDB, Shell scripting, data profiling, API integration, and data flow documentation)
Required: Demonstrated experience with AI tools such as GPT and Gemini, with clear business use cases highlighted on resume
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
Required: Experience working in an onshore/offshore support model, collaborating with offshore teams
Preferred: GCP Google Cloud Professional Data Engineer Certification
Preferred: Experience with SAFe methodology
Preferred: Experience working with GitHub, RTC, and automation tools