Key Skills: Bigquery, Airflow, Python, GCP, Semantic Search, DBT, Pub/Sub, SQL, Metadata
Roles and Responsibilities:
- Develop and maintain production data pipelines on GCP with strong focus on data product development and reusable components.
- Implement transformations and standardized data models using DBT, ensuring reliable and scalable downstream consumption.
- Build and operate workflow orchestration using Airflow/Cloud Composer, including scheduling, monitoring, and troubleshooting.
- Develop ingestion and serving logic in BigQuery using Python and SQL, optimizing for performance and correctness.
- Support semantic search and AI-ready data enablement patterns, including data preparation for ML/GenAI consumption.
Skills Required:
- 3-6 years of experience in GCP-based data platform development and production data pipeline implementation.
- Hands-on data product development and implementation experience in cloud data engineering workflows.
- Strong GCP experience including BigQuery and Airflow (Cloud Composer) for orchestration.
- Proficiency in Python and SQL for building and maintaining production data pipelines and transformations.
- DBT for transformation workflows and semantic search enablement using production-grade data models.
Good to Have:
- Additional cloud exposure (AWS/Azure) and familiarity with AI/ML data enablement patterns.
Education: B.E., B.Tech, B.Tech M.Tech (Dual), MCA, M.E., M. Tech in Computer Engineering/Computer Science/Computer Application/Computer Science and Automation/Computer Science and Information Security/Computer Science and Technology/Computer Science Engineering/Computer Technology (or equivalent).
