Descripción de la oferta
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. Meet Our Recruitment Process Each step helps us understand your skills and overall fit. If it's a match, you'll receive an offer. #J-18808-Ljbffr
