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Hybrid
Full Time
Experience Level: 10 to 12 years of relevant IT experience
Key Responsibilities:
Design, develop, test, and maintain scalable ETL data pipelines using Python.
Architect the enterprise solutions with various technologies like Kafka, multi-cloud services, auto-scaling using GKE, Load balancers, APIGEE proxy API management, DBT, using LLMs as needed in the solution, redaction of sensitive information, DLP (Data Loss Prevention) etc.
Work extensively on Google Cloud Platform (GCP) services such as:
Dataflow for real-time and batch data processing
Cloud Functions for lightweight serverless compute
BigQuery for data warehousing and analytics
Cloud Composer for orchestration of data workflows (on Apache Airflow)
Google Cloud Storage (GCS) for managing data at scale
IAM for access control and security
Cloud Run for containerized applications Should have experience in the following areas :
API framework: Python FastAPI
Processing engine: Apache Spark
Messaging and streaming data processing: Kafka
Storage: MongoDB, Redis/Bigtable
Orchestration: Airflow
Experience in deployments in GKE, Cloud Run.
Perform data ingestion from various sources and apply transformation and cleansing logic to ensure high-quality data delivery.
Implement and enforce data quality checks, validation rules, and monitoring.
 
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