Data Engineer ID89384

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 PySpark, advanced SQL, hands-on GCP experience, and experience with Delta Lake and modern 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 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 reusable frameworks and components to support new business requirements and datasets across multiple 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, troubleshooting, and ongoing enhancement of data and agentic solutions. • Collaborate with business, data engineering, and platform teams to identify further automation opportunities.