Lead GCP AI Data Engineer/Architect

DXC Technology

3 - 8 years

5 - 10 Lacs

bengaluru

Posted:6 hours ago| Platform:

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Skills Required

performance tuning orchestration data modeling gcp social media machine learning data processing apache monitoring python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Lead GCP AI Data Engineer/Architect

Job Location: Hyderabad / Bangalore / Chennai / Kolkata / Noida/ Gurgaon / Pune / Indore / Mumbai

Key Responsibilities

AI/ML Solution Development: Design, build, train, and deploy scalable machine learning models and AI agents using Vertex AI , including Generative AI Studio, Model Garden, and custom training pipelines.
Agentic AI Systems: Develop and manage intelligent agents and multi-agent systems using frameworks like Agentspace and the Google AI Development Kit (ADK) to automate complex workflows and create intelligent applications.
Data Pipeline Orchestration: Architect, build, and maintain robust, scalable data processing pipelines and workflows using Cloud Composer (Apache Airflow) to handle data ingestion, transformation, and model training schedules.
Large-Scale Data Processing: Implement efficient data processing jobs and streaming pipelines using Dataflow to handle large-scale datasets for analytics and ML model feeding.
Data Warehousing Analytics: Utilize BigQuery for data storage, warehousing, and advanced analytics. Design schemas, optimize queries, and leverage BigQuery ML for in-database machine learning.
MLOps Implementation: Implement MLOps best practices for model versioning, continuous integration/continuous delivery (CI/CD), monitoring, and governance to ensure the reliability and scalability of our AI solutions.

Required Qualifications

Proven GCP Experience: 3+ years of hands-on experience designing and implementing solutions on Google Cloud Platform.
Vertex AI Proficiency: Demonstrated experience with the Vertex AI platform, including building custom models, using AutoML, and deploying endpoints. Solid understanding of the end-to-end ML lifecycle on GCP.
Data Engineering Expertise: Strong experience in building and orchestrating data pipelines using Cloud Composer and Dataflow .
BigQuery Mastery: In-depth knowledge of BigQuery , including data modeling, performance tuning, and writing complex SQL queries.
Programming Skills: High proficiency in Python and experience with relevant libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Apache Beam).

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