Data Engineer Id89384

Agileengine

Victoria

Presencial

ARS 136.863.000 - 228.106.000

Jornada completa

hace 45 horas
Sé de los primeros/as/es en solicitar esta vacante
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Ventajas ofrecidas por este puesto de trabajo

Professional growth
Competitive USD-based compensation
A selection of exciting projects
Flextime

Descripción de la vacante

Agileengine is seeking a Data Engineer with strong Databricks, PySpark and GCP experience to design scalable ETL/ELT pipelines and productionize agentic workflows for data automation. You will design and optimize data pipelines, integrate with BigQuery/Delta Lake environments, build reusable components, and ensure data quality and production readiness across projects.

Ideal candidates have 5+ years of hands-on experience, advanced SQL skills, and a passion for scalable, reliable data solutions

Formación

  • 5+ years hands-on Databricks and PySpark experience.
  • Advanced SQL and data-processing skills required.
  • GCP experience, especially BigQuery, is essential.
  • Delta Lake and lakehouse architectures familiarity.
  • ETL/ELT design, performance tuning, and data quality focus.
  • Proven ability to build reliable, scalable data solutions.
  • Strong analytical and troubleshooting capabilities.
  • Knowledge of software engineering practices (tests, version control, deployment, monitoring).

Responsabilidades

  • Design, develop, and optimize scalable ETL/ELT pipelines using Databricks, PySpark, and SQL.
  • Build agentic workflows to automate data engineering and operations.
  • Integrate Databricks, GCP, BigQuery, and Delta Lake environments.
  • Develop pipelines to support new business requirements and datasets.
  • Create reusable data engineering frameworks across use cases.
  • Implement data quality checks, monitoring, and production controls.
  • Optimize PySpark/SQL workloads for performance and reliability.
  • Support testing, deployment, and productionizing of data solutions.
  • Troubleshoot complex data and production issues with sustainable fixes.
  • Collaborate with multiple teams to identify further automation opportunities.

Conocimientos

Databricks
PySpark
Advanced SQL
GCP BigQuery
Delta Lake
ETL/ELT design
Production-grade data solutions
Troubleshooting

Herramientas

Databricks
BigQuery
Delta Lake
PySpark

Descripción del empleo

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a Data Engineer with strong Databricks and GCP experience to develop scalable ETL/ELT pipelines and productionize agentic workflows for data engineering automation.

WHAT YOU WILL DO
  • Design, develop, and optimize scalable ETL/ELT data pipelines using Databricks, PySpark, and SQL.
  • Build and operationalize agentic workflows to automate data engineering and operational processes such as data validation, issue identification, troubleshooting, and workflow execution.
  • Integrate agentic capabilities with existing 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.
MUST HAVES
  • 5+ years of strong hands-on experience with Databricks and PySpark.
  • Advanced SQL and data-processing skills.
  • Hands-on experience with GCP, particularly BigQuery.
  • Experience with Delta Lake and modern data lake/lakehouse architectures.
  • Strong understanding of ETL/ELT, data pipeline design, performance optimization, and data quality.
  • Experience building reliable, scalable, production-grade data solutions.
  • Strong analytical and troubleshooting skills.
  • Understanding of software engineering practices, including testing, version control, deployment, monitoring, and production support.
NICE TO HAVES
  • Experience developing or integrating AI/agentic workflows, AI agents, or workflow automation solutions.
  • Experience applying AI to automate data engineering, validation, troubleshooting, or operational processes.
  • Familiarity with orchestration and automation frameworks.
  • Experience developing reusable data engineering frameworks and platform components.
  • Exposure to productionizing AI-enabled solutions with appropriate validation, monitoring, and human oversight.
PERKS AND BENEFITS
  • Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
  • Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
  • A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
  • Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.
Consigue la evaluación confidencial y gratuita de tu currículum.

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