Senior Data Engineer - Remote/Hybrid Data Platform Architect

AgileEngine, LLC.

León

Híbrido

MXN 900.000 - 1.200.000

Jornada completa

14 días+

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Envía un currículum específico para el puesto de trabajo en cuestión de minutos.

Ventajas ofrecidas por este puesto de trabajo

Professional growth
Competitive compensation (USD-based)
Flextime: remote and office options
Exciting projects

Descripción de la vacante

AgileEngine, LLC. is seeking a Senior Data Engineer to design, build, and scale a modern data platform. You will architect ETL/ELT pipelines, optimize Snowflake schemas, and enforce DataOps practices with CI/CD, Docker, and automated testing.

You will orchestrate workflows with Airflow, Prefect, or Dagster, ingest data from REST APIs and event streams, and emphasize clean, well-tested Python code for reliability and accessibility.

Formación

  • 4+ years of experience as a Data Engineer.
  • Proficiency in Python with well-tested code.
  • SQL, data modeling, and Snowflake schemas.
  • Experience with REST APIs, event-driven sources, and pipelines.

Responsabilidades

  • Design, build, and maintain scalable ETL/ELT workflows.
  • Create production-ready Snowflake schemas for analytics.
  • Ingest data from REST APIs, event streams, and batch sources.
  • Maintain Airflow/Prefect/Dagster pipelines and CI/CD.
  • Implement data quality checks, lineage, and alerting.
  • Follow Git, Docker, and IaC practices and document clearly.

Conocimientos

Python
SQL
Snowflake
Apache Airflow
Prefect
Dagster
REST APIs
Git
Docker
CI/CD
Infrastructure-as-Code
Data quality checks
Data lineage

Herramientas

Airflow
Prefect
Dagster
Snowflake
Git
Docker

Descripción del empleo

AgileEngine, LLC. is seeking a Senior Data Engineer to design, build, and scale a modern data platform. You will architect ETL/ELT pipelines, optimize Snowflake schemas, and enforce DataOps practices with CI/CD, Docker, and automated testing.

You will orchestrate workflows with Airflow, Prefect, or Dagster, ingest data from REST APIs and event streams, and emphasize clean, well-tested Python code for reliability and accessibility.

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