Senior Data Engineer

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NextHire

πŸ“Remote - India

Summary

Join our team as a Senior Data Engineer and build scalable, reliable data pipelines on Google Cloud Platform (GCP). You will leverage your expertise in DBT, SQL, and data transformation to architect and maintain robust data workflows. Collaborate with stakeholders to define data requirements and optimize workflows for performance and cost-effectiveness. Ensure high standards in documentation, testing, and version control. Contribute to team best practices and continuous improvement. This remote/hybrid role requires 4+ years of data engineering experience, including 2+ years with GCP and 1+ year with DBT. Strong SQL skills and a deep understanding of data modeling are essential.

Requirements

  • 4+ years in data engineering or a related role
  • 2+ years of experience working with GCP services (e.g., BigQuery, GCS, Dataflow)
  • 1+ year of hands-on experience with DBT
  • Proficient in SQL and data modeling concepts
  • Experience with orchestration tools like Apache Airflow or Cloud Composer
  • Strong understanding of data pipelines, modularity, and maintainability
  • Ability to gather business requirements and translate them into technical solutions

Responsibilities

  • Design, develop, and maintain ETL/ELT pipelines on Google Cloud Platform
  • Use DBT to transform and manage clean, modular, and reusable data models
  • Collaborate with business stakeholders to define and refine data requirements
  • Leverage Apache Airflow or Cloud Composer for workflow orchestration
  • Work with various cloud data warehouses such as BigQuery, Snowflake, or Redshift
  • Optimize data workflows for performance, reliability, and cost-effectiveness
  • Ensure high standards in documentation, testing, and version control
  • Contribute to and promote team best practices, code reviews, and continuous improvement

Preferred Qualifications

  • GCP certification (Associate Cloud Engineer or higher)
  • Experience working in multi-cloud environments (GCP + AWS)
  • Familiarity with CI/CD pipelines, version control systems like Git, and DevOps practices in data projects

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