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.

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.
- 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.

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.

Requirements
Strong hands-on experience with Databricks and PySpark. Advanced SQL and data-processing skills. Hands-on experience with Google Cloud Platform (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.

📌 Data Engineer (Rosarito)
🏢 Agileengine
📍 Rosarito