Data Engineer ID89383

AgileEngine, LLC.

Porto

Hybrid

EUR 50,000 - 70,000

Full time

3 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 design, develop, and productionize scalable ETL/ELT pipelines and agentic workflows.

You will work across Databricks, GCP, BigQuery, and Delta Lake, building reusable data engineering components and ensuring data quality. The role emphasizes scalable data solutions, performance optimization, and collaboration with cross-functional teams to automate data workflows and support evolving business needs.

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 lake architectures.
  • Strong ETL/ELT, pipeline design, performance optimization, and data quality.
  • Production-grade data solutions development.
  • Strong analytical and troubleshooting abilities.
  • Understanding of software engineering practices (testing, VCS, deployment, monitoring).

Responsibilities

  • Design, develop, and optimize scalable ETL/ELT data pipelines.
  • Build and operationalize agentic workflows to automate data processes.
  • Integrate agentic capabilities with Databricks, GCP, BigQuery, and Delta Lake.
  • Develop pipelines and solutions for new business requirements.
  • Build reusable frameworks across multiple data use cases.
  • Implement data quality checks, monitoring, validation, and production controls.
  • Optimize PySpark and SQL workloads for performance and scalability.
  • Support testing, deployment, productionization and enhancements.
  • Troubleshoot complex data and production issues.
  • Collaborate with business and platform teams to identify more automation.

Skills

Databricks
PySpark
Advanced SQL
BigQuery
Delta Lake
ETL/ELT
Data pipelines
Data quality
Testing & deployment
Version control
Production support
Troubleshooting
Automation

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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