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Job Description
Structured overview of role & requirementsAbout This Role
Architect and implement scalable ETL/ELT pipelines, big data solutions on Google BigQuery and GCP.
Build and maintain MLOps pipelines and generative AI workflows using tools such as LangChain and Airflow.
Lead L3 support for GCP and BigQuery platform issues, including root cause analysis and performance optimization.
Minimum Requirements
4 to 5 years of hands-on experience with Google BigQuery, ETL processes, AI & ML apps, and MLOps focused on GCP.
Strong proficiency in Google Cloud Platform services and governance tools; familiarity with multi-cloud environments preferred.
Advanced skills in Python (3.10+), Shell scripting (Linux CLI), AppScript (JavaScript), and frameworks like FastAPI, Django REST, Pandas, LangChain.
Experience with relational databases (MySQL 8+, PostgreSQL 13+), Firestore, BigQuery, and tools for CI/CD such as GitHub Actions and Cloud Build.
Ideal Candidate Profile
Experienced in designing and managing large-scale data architectures with a focus on performance, cost optimization, and security on cloud platforms.
Skilled in operational support and incident management at senior L3 escalation level for complex cloud data environments.
Comfortable working in Agile/Kanban environments using Jira and source control with GitHub, capable of enforcing coding and deployment standards.