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Tech Stack
Tools & technologiesAirflowApacheBigQueryCloudGoogle Cloud PlatformJavaPySparkPythonSQL
About the role
Key responsibilities & impact- Design, develop, and maintain scalable batch and real-time data pipelines on GCP
- Implement and manage Medallion Architecture (Bronze, Silver, Gold layers) for data processing
- Build high-performance data transformations using Python and PySpark
- Develop and optimize complex SQL queries for analytical workloads
- Work extensively with BigQuery for large-scale data processing and performance tuning
- Develop and deploy pipelines using Cloud Dataflow
- Orchestrate workflows using Cloud Composer (Apache Airflow)
- Manage data storage and lifecycle using Google Cloud Storage (GCS)
- Implement version control and CI/CD pipelines using Git-based tools
- Ensure data security, governance, and access control using GCP IAM
- Optimize data solutions for performance, scalability, reliability, and cost-efficiency
Requirements
What you’ll need- Strong hands-on experience with Google Cloud Platform (GCP)
- Expertise in BigQuery (partitioning, clustering, query optimization)
- Proven experience implementing Medallion Data Architecture
- Strong programming skills in Python and PySpark
- Hands-on exposure on Java
- Advanced proficiency in SQL (complex joins, window functions, performance tuning)
- Hands-on experience with Cloud Dataflow
- Experience with Cloud Composer (Airflow) for orchestration
- Experience working with Google Cloud Storage (GCS)
- Knowledge of version control systems (Git) and CI/CD practices
- Strong understanding of GCP IAM and cloud security best practices
Benefits
Comp & perks- Health insurance
- Flexible work arrangements
ATS Keywords
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Hard Skills & Tools
PythonPySparkSQLJavaBigQueryCloud DataflowCloud ComposerGoogle Cloud StorageCI/CDMedallion Architecture
