Senior Data Engineer - Databricks & GCP, Flexible Hours

Agileengine

Rosarito

Presencial

MXN 1.455.000 - 2.182.000

Jornada completa

Hace 7 días

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Descripción de la vacante

AgileEngine is seeking a Data Engineer with strong Databricks and GCP experience to design scalable ETL/ELT pipelines and productionize agentic workflows for data automation. You will implement data quality checks, optimize PySpark/SQL workloads, and collaborate across data, platform, and business teams to deliver reliable data solutions for Fortune 500 brands and cutting-edge startups.

Join a people-first culture with growth opportunities, flexible work options, and competitive USD-based

Formación

5+ years of hands-on Databricks and PySpark experience.
Strong SQL and data-processing skills.
Hands-on GCP experience, especially BigQuery.
Experience with Delta Lake and modern lakehouse architectures.
Understanding of ETL/ELT, data pipelines, and data quality.
Experience delivering production-grade data solutions.
Strong analytical and troubleshooting abilities.
Knowledge of software engineering practices (testing, version control, deployment, monitoring).
Upper-intermediate English.

Responsabilidades

Design, develop, and optimize scalable ETL/ELT data pipelines using Databricks, PySpark, and SQL.
Build and operationalize agentic workflows to automate data engineering processes.
Integrate agentic capabilities with Databricks, GCP, BigQuery, and Delta Lake environments.
Develop data pipelines and processing solutions to support new business requirements and datasets.
Build reusable frameworks and components that can be leveraged across multiple data engineering and business use cases.
Implement data quality checks, monitoring, validation, exception handling, and production controls.
Optimize PySpark and SQL workloads for performance, reliability, and scalability.
Support testing, deployment, productionization, and ongoing enhancement of data and agentic solutions.
Troubleshoot complex data and production issues and implement sustainable solutions.
Collaborate with business, data engineering, and platform teams to identify further automation opportunities.