Data Engineer ID89384

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.

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

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.

- 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.

- 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.

- 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.

- 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.

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.