Senior Data Engineer – Platform, Automation & AI Acceleration (GCP)

New

JobgetherData engineering

This is a fully remote opportunity ... based in Brazil.Full-TimeSenior

Salary not disclosed

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Job Details

Have solid data engineering experience on Google Cloud Platform, particularly with BigQuery, Cloud Composer/Airflow, Dataflow, Cloud Run, Cloud Functions, and Cloud Workflows.
Have advanced proficiency in Python and SQL, including automation, internal tooling, APIs, and GCP SDKs.
Have experience implementing CI/CD pipelines using GitHub Actions, GitLab CI, or Cloud Build.
Have practical experience with Terraform, Infrastructure as Code, and DataOps.
Know SQL analysis and validation tools such as SQLFluff and SQLGlot.
Have experience developing and maintaining automated pipelines, tests, schema validation, and data governance mechanisms.
Have hands-on experience with AI-assisted development tools, particularly Antigravity, for code generation and validation.
Nice to have: experience with Dataform or dbt, including unit testing, ephemeral environments, and Slim CI.
Nice to have: knowledge of SQL Abstract Syntax Trees, data lineage, and automated anti-pattern detection.
Nice to have: experience developing AI agents, Model Context Protocol servers, IDE extensions, or automated Pull Request code review bots.
Nice to have: knowledge of BigQuery cost and performance optimization, including BigQuery Editions and slot consumption.
Nice to have: experience with Golden Paths, Golden Modules, and Platform Engineering.

Develop AI-assisted workflows with Antigravity, including context libraries, templates, tools, and validation mechanisms.
Build and maintain CI/CD pipelines with automated SQL validation, contract testing, schema checks, data quality controls, and performance testing.
Implement BigQuery cost analysis and query optimization using tools such as Dry Run and Query Explain.
Design Terraform infrastructure-as-code solutions and reusable modules for GCP resources, permissions, and governance policies.
Improve orchestration using Cloud Composer/Airflow, Cloud Workflows, Eventarc, and Pub/Sub.
Integrate data engineering, automation, and AI tools into development workflows, including automated Pull Request validations.
Improve Developer Experience by reducing manual tasks, rework, and delivery-cycle time.
Promote engineering practices supporting platform reliability, scalability, governance, and cost optimization.

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