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4 Days ago

Job Opening for GCP Data Engineer Lead (Job Code RT 1413).

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Bangalore, Karnataka, India
Information Technology
Full-Time
Radical Technologies

Overview

Apply Online

Interested candidates kindly apply before 14/04/2025.

CV must be in PDF format, saved with your Full name.

Hiring for GCP Data Engineer Lead!!!

Job Title: GCP Data Engineer Lead (811 Years Experience)

Immediate Joiners Or Who Can Join In 15 Days

BGV is mandatory

Total Number of Years of Experience: 5-8 Years

Location: Pune, Bengaluru, Noida, Bhopal, Chennai, New Mumbai, Hyderabad

Employment Type: Full-Time

Mode: Hybrid (3 days work from office mandatory)

Key Responsibilities

  • Design and implement scalable, resilient, and high-performance data pipelines on Google Cloud Platform (GCP) using BigQuery, Cloud Composer (Airflow), Pub/Sub, and Dataflow.
  • Build and maintain both batch and streaming data pipelines to support analytics, reporting, and real-time decision-making.
  • Develop and manage complex Airflow DAGs via Cloud Composer for workflow orchestration and job scheduling.
  • Write robust, modular, and efficient Python code and advanced SQL queries for data ingestion, transformation, and aggregation.
  • Work extensively with Pub/Sub for real-time data streaming and message-based integrations.
  • Optimize BigQuery datasets and SQL queries for performance, scalability, and cost-efficiency.
  • Leverage Cloud Functions, Cloud Storage, and other GCP services as part of end-to-end data workflows.
  • Implement monitoring, logging, and alerting for data pipelines using Cloud Logging (Stackdriver) and other observability tools.
  • Apply best practices for data security, governance, and compliance in cloud-based environments.
  • Use Terraform or similar IaC tools for infrastructure automation and deployment.
  • Collaborate with cross-functional teams (data science, analytics, business) to deliver reliable and timely data solutions.
  • Mentor junior engineers and contribute to the development of engineering standards and architecture reviews.
  • Contribute to the continuous improvement of CI/CD pipelines and DevOps practices for data engineering.
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