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
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5+ years of strong hands-on experience with Databricks and PySpark.
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Advanced SQL and data-processing skills.
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Hands-on experience with GCP, particularly BigQuery.
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Experience with Delta Lake and modern data lake/lakehouse architectures.
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Strong understanding of ETL/ELT, data pipeline design, performance optimization, and data quality.
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Experience building reliable, scalable, production-grade data solutions.
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Strong analytical and troubleshooting skills.
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Understanding of software engineering practices, including testing, version control, deployment, monitoring, and production support.
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Upper-intermediate English level.
NICE TO HAVES
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Experience developing or integrating AI/agentic workflows, AI agents, or workflow automation solutions.
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Experience applying AI to automate data engineering, validation, troubleshooting, or operational processes.
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Familiarity with orchestration and automation frameworks.
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Experience developing reusable data engineering frameworks and platform components.
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Exposure to productionizing AI-enabled solutions with appropriate validation, monitoring, and human oversight.
WHAT YOU WILL DO
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Design, develop, and optimize scalable ETL/ELT data pipelines using Databricks, PySpark, and SQL.
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Build and operationalize agentic workflows to automate data engineering and operational processes such as data validation, issue identification, troubleshooting, and workflow execution.
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Integrate agentic capabilities with existing Databricks, GCP, BigQuery, and Delta Lake environments.
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Develop data pipelines and processing solutions to support new business requirements and datasets.
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Build reusable frameworks and components that can be leveraged across multiple data engineering and business use cases.
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Implement data quality checks, monitoring, validation, exception handling, and production controls.
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Optimize PySpark and SQL workloads for performance, reliability, and scalability.
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Support testing, deployment, productionization, and ongoing enhancement of data and agentic solutions.
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Troubleshoot complex data and production issues and implement sustainable solutions.
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Collaborate with business, data engineering, and platform teams to identify further automation opportunities.
PERKS AND BENEFITS
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Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
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Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
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Exciting projects: Modern solutions with Fortune 500 and top product companies.
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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.