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Mid-level data role, Bangalore metro, popular toolset and strong global brand increase applicant competition.
Core data engineering skills are highly transferable across industries despite GCP/dbt specifics.
Explicit 5+ years and mandatory GCP, Airflow, dbt, Spark and tooling requirements create strict filters.
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Build, deploy, and maintain cloud-native applications and data pipelines on Google Cloud Platform using Python and SQL, ensuring reliability and performance optimization.
Manage cloud infrastructure using Infrastructure as Code (e.g., Terraform) and automate deployments with CI/CD pipelines such as GitHub Actions or Cloud Functions.
Collaborate with stakeholders to gather requirements and deliver data-driven solutions, maintain application health, and participate in code reviews and team knowledge sharing.
Formal qualifications in computer science, software engineering, or equivalent engineering discipline.
Minimum 5 years of experience as a software engineer or data engineer in agile teams.
Strong programming skills in Python and advanced SQL, with hands-on experience in modern data platforms and orchestration tools (Apache Airflow, dbt, Apache Spark).
Experience with Google Cloud Platform services (BigQuery, CloudSQL, Pub/Sub) and infrastructure automation tools like Terraform.
Experienced in cloud-native application development and data engineering on Google Cloud Platform, with capability to manage end-to-end data pipelines and integrations.
Skilled in DevOps practices including CI/CD automation, infrastructure as code, and monitoring to ensure production stability and performance.
Ability to engage cross-functional teams effectively to translate business needs into technical solutions using modern technologies and tools.