Description

Design and maintain scalable ETL/ELT data pipelines and data warehouses on Google Cloud Platform.

This role is on-site.

Responsibilities

• Build and optimize data lakes and warehouses using BigQuery and Cloud Storage.
• Develop production-grade ETL pipelines with Dataflow, Dataproc, and Pub/Sub.
• Orchestrate workflows using Cloud Composer and manage transformations with dbt or Dataform.
• Integrate and deploy AI/ML models using Vertex AI.
• Ensure data platform reliability, security, and cost-efficiency.

Required Skills

• 7+ years of software engineering experience with a focus on data engineering.
• Extensive hands-on experience with Google Cloud Platform services.
• Proficiency in Python and SQL for backend development and data engineering.
• Strong understanding of data warehousing concepts, including star/snowflake schema modeling.
• Experience with BigQuery, Cloud Dataflow, Dataproc, and Cloud Composer.
• Proven ability to build scalable, cost-optimized data solutions.

Preferred Skills

• Google Cloud Professional Data Engineer or Machine Learning Engineer certification.
• Experience with MLOps practices, model monitoring, and RAG/LLM applications.
• Familiarity with containerization (Docker) and orchestration (Kubernetes/GKE).

Key Skills

Education

Any Gradute