Data Engineer ID89384

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

Benefits offered by this job

Professional growth

Competitive compensation

Exciting projects

Flextime

Job summary

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

You will design, build and optimize data pipelines across Databricks, PySpark, SQL, and BigQuery, and collaborate with cross-functional teams to expand automation opportunities and ensure data quality.

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 modern lakehouse architectures.
• Strong ETL/ELT design, data pipeline performance optimization and data quality.
• Experience building reliable, scalable production data solutions.
• Strong analytical and troubleshooting abilities.
• Understanding of software engineering practices including testing, version control, deployment and production support.
• Upper-intermediate English level.

Responsibilities

• Design, develop, and optimize scalable ETL/ELT data pipelines with 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 to support new business requirements and datasets.
• Create reusable frameworks and components for data engineering and business use cases.
• Implement data quality checks, monitoring, validation, exception handling and production controls.
• Optimize PySpark and SQL workloads for performance and reliability.
• Support testing, deployment, productionization and ongoing enhancement of data and agentic solutions.
• Troubleshoot complex data and production issues with sustainable solutions.
• Collaborate with business, data engineering and platform teams to identify automation opportunities.

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.