The Role
Develop and optimize scalable ETL/ELT pipelines using Databricks, PySpark, and SQL. Build production-grade data solutions and agentic workflows for validation, troubleshooting, automation, and operational processes across GCP, BigQuery, and Delta Lake environments. Implement data quality controls, monitoring, testing, deployment, and production support while improving performance and reliability. Collaborate with business, data engineering, and platform teams to identify automation opportunities.
Summary Generated by Built In
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.
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.
Skills Required
- 5+ years of strong hands-on experience with Databricks and PySpark
- Advanced SQL and data-processing skills
- Hands-on experience with Google Cloud Platform, particularly BigQuery
- Experience with Delta Lake and modern data lake or 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 proficiency
- Experience developing or integrating AI or 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 validation, monitoring, and human oversight
Similar Jobs
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
AgileEngine is a privately held company established in 2010 that builds dedicated teams of designers and developers. We turn good ideas into awesome software that people actually want to use. Some of the biggest names and the hottest startups around the world chose us to build their tech.
