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.

The mandatory requirements are 5+ years of experience with Databricks and GCP, advanced SQL, and experience with Delta Lake and lakehouse architectures, along with an upper-intermediate English level. Experience building AI agents is a plus.

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 solid 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

- Remote work & Local connection: Work where you feel most productive and connect with your team in periodic meet-ups to strengthen your network and connect with other top experts.
- Legal presence in India: We ensure full local compliance with a structured, secure work environment tailored to Indian regulations.
- Competitive Compensation in INR: Fair compensation in INR with dedicated budgets for your personal growth, education, and wellness.
- Innovative Projects: Leverage the latest tech and create cutting-edge solutions for world-recognized clients and the hottest startups.

📌 Data Engineer (India)
🏢 AgileEngine
📍 India