Data Engineer ID89384

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 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 Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized Well-being & support: access local well-being programs and people-focused support tailored to your location Job Type: Full-time Work Location: Remote