Data Engineer ID89383

AgileEngine, LLC.

Madrid

Hybrid

EUR 65,000 - 98,000

Full time

5 days ago
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Benefits offered by this job

Professional growth
Competitive compensation
Exciting projects
Flextime

Job summary

AgileEngine, LLC. is seeking a Data Engineer with strong Databricks and GCP experience to build scalable ETL/ELT pipelines and productionize agentic workflows for data engineering automation.

Ideal candidates have 5+ years with Databricks, PySpark, SQL proficiency, and hands-on BigQuery experience within modern lakehouse architectures. Remote-friendly and client-focused projects await.

Qualifications

  • 5+ years of hands-on Databricks and PySpark experience.
  • Advanced SQL and data-processing skills.
  • Hands-on GCP experience, especially BigQuery.
  • Experience with Delta Lake and data lakehouse architectures.
  • Strong ETL/ELT, data pipeline design, performance optimization and data quality.
  • Production-grade data solutions experience.
  • Solid analytical and troubleshooting skills.
  • Understanding of software engineering practices: testing, VCS, deployment, monitoring, and production support.

Responsibilities

  • 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.
  • Integrate agentic capabilities with Databricks, GCP, BigQuery, and Delta Lake environments.
  • Develop data pipelines and processing solutions for new business requirements and datasets.
  • Create reusable frameworks and components for multiple data use-cases.
  • Implement data quality checks, monitoring, validation, and production controls.
  • Optimize PySpark and SQL workloads for performance and reliability.
  • Support testing, deployment, productionization, and ongoing enhancements.
  • Troubleshoot complex data and production issues and implement sustainable solutions.
  • Collaborate with business, data engineering, and platform teams to identify automation opportunities.

Skills

Databricks
PySpark
SQL
BigQuery
Delta Lake
ETL/ELT
Data pipelines

Tools

BigQuery

Job description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

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.

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.
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.
PERKS AND BENEFITS
  • Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
  • Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
  • Exciting projects: Modern solutions with Fortune 500 and top product companies.
  • Flextime: Flexible schedule with remote and office options.
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