Data Engineer ID89384

AgileEngine; Madrid; Hybrid; EUR 60,000 - 90,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation

Exciting projects

Flextime

Job summary

AgileEngine is hiring a Data Engineer to design, build, and scale ETL/ELT pipelines using Databricks and PySpark. You will productionize agentic workflows and integrate with GCP, BigQuery, and Delta Lake in a data-driven environment.

The role requires 5+ years in Databricks/PySpark, advanced SQL, and strong data engineering fundamentals. English level is upper-intermediate; remote-friendly with a hybrid setup in Madrid offices.

Qualifications

• 5+ years hands-on experience with Databricks and PySpark
• Advanced SQL and data-processing skills
• Hands-on with GCP, particularly BigQuery
• Experience with Delta Lake and modern data lake architectures
• Strong ETL/ELT, data pipeline design, and data quality
• Production-grade data solutions development experience
• Strong analytical and troubleshooting skills
• Understanding of software engineering practices including testing, version control, deployment, monitoring
• Upper-intermediate English level

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 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.

Skills

Databricks

PySpark

SQL

BigQuery

Delta Lake

ETL/ELT

Data pipelines

Performance tuning

Data quality

Production support

Testing & VCS

Tools

Databricks

BigQuery

Delta Lake

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.
• Upper-intermediate English level.

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.

Meet Our Recruitment Process

Application -> Coding Challenge -> Video Interview -> Technical Interview or Hiring Manager Interview

Each step helps us understand your skills and overall fit.

If it's a match, you'll receive an offer.