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Data Engineer ID89383
AgileEngine
Source: Headcount Labs · original listing ↗
Job data: Headcount Labs, ODbL 1.0. Job descriptions belong to their employers.
Source date: 10/26/2026
About this role
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.