Job Description

We are looking for a Data Engineer with strong Databricks and GCP experience to build scalable ETL/ELT pipelines and productionize agentic workflows for data engineering automation. The mandatory requirements are 5+ years of hands-on Databricks and PySpark experience, advanced SQL skills, strong GCP and BigQuery knowledge, and experience with Delta Lake and lakehouse architectures. RECRUITMENT PROCESS 1. Application — Share a few details about your experience and background. 2. Coding Challenge — If applicable, complete it in the coding language you are most comfortable with. 3. Video Interview — Record a short video introduction in English. 4. Technical Interview or Hiring Manager Interview — Discuss your experience and fit for the role. 5. Offer — If it’s a match, you’ll receive an offer. WHAT YOU’LL GAIN - Remote work — Work from where you feel most productive. - Local presence in India — Work in a structured and compliant environment aligned with Indian regulations. - Competitive compensation in INR — Receive compensation in INR, plus support for learning, education, and wellness. - Exciting projects — Work with modern technologies for global clients and fast-growing companies. 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 pipelines using Databricks, PySpark, and SQL. - Build and operationalize agentic workflows that automate data validation, issue identification, troubleshooting, and workflow execution. - Integrate agentic capabilities with Databricks, GCP, BigQuery, and Delta Lake environments while supporting new business requirements and datasets. - Build reusable frameworks and components that can support multiple data engineering and business use cases. - Implement data quality checks, monitoring, validation, exception handling, and production controls. - Optimize PySpark and SQL workloads and support testing, deployment, productionization, and ongoing enhancement of data and agentic solutions. - Troubleshoot complex production issues and collaborate with business, data engineering, and platform teams to identify additional automation opportunities.