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About the role
About the Role We are looking for a highly skilled Data Engineer with strong Google Cloud Platform (GCP) expertise to design, develop, and maintain scalable data solutions. The ideal candidate will have hands-on experience in building robust ETL/ELT frameworks, real-time and batch data pipelines, data modeling, and leveraging modern GCP services to support analytics and business intelligence initiatives. Key Responsibilities Design, develop, and optimize scalable data pipelines on GCP. Build and maintain batch, event-driven, and real-time data ingestion and processing frameworks . Develop robust ETL/ELT pipelines for integrating data from multiple internal and external sources. Design and implement efficient data models to support reporting, analytics, and data science use cases. Create and manage data orchestration workflows using Cloud Composer (Apache Airflow) . Develop event-driven architectures using Pub/Sub , Cloud Functions , and other cloud-native services. Optimize data storage, transformation, and querying performance using BigQuery . Ensure data quality, consistency, governance, and security best practices. Collaborate with Data Analysts, Data Scientists, Architects, and business stakeholders to translate requirements into scalable solutions. Monitor, troubleshoot, and improve data platform performance and reliability. Required Skills & Experience GCP Services (Must Have) Hands-on experience with one or more of the following GCP services: BigQuery Cloud Composer (Airflow) Pub/Sub Cloud Functions Cloud Storage Dataflow Cloud Run (good to have) Core Technical Skills Strong experience in designing and implementing data models (Star Schema, Snowflake Schema, Dimensional Modeling). Proven experience in building and maintaining ETL/ELT pipelines . Expertise in developing: Batch-based data pipelines Event-driven data pipelines Real-time/streaming data pipelines Advanced SQL skills with performance tuning experience. Strong Python programming experience for data engineering workflows. Experience working with structured and semi-structured data formats (JSON, Parquet, Avro, CSV). Knowledge of data warehousing concepts and best practices.
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