Data Engineer - AI/ML

This role requires candidates who are currently authorized to work in the U.S. without sponsorship, and C2C arrangements are not accepted. This role is onsite near Tustin, CA.We are seeking a highly experienced Sr. Data Platform Engineer to help build, mature, and scale a modern enterprise data platform. This role combines advanced data engineering with platform development and the productionization of AI/ML capabilities.The ideal candidate has experience working in greenfield or major modernization environments and is comfortable establishing architecture, engineering standards, and scalable patterns rather than simply working within an existing platform.ResponsibilitiesDesign, build, and optimize modern data platforms using technologies such as Databricks, Spark/PySpark, SQL, and cloud-based data services.Develop scalable data pipelines, orchestration frameworks, and reusable platform capabilities supporting analytics and data products.Help establish architecture standards, engineering patterns, governance, monitoring, reliability, and development best practices.Support the deployment and productionization of AI/ML workloads, including the infrastructure and processes required to scale, govern, monitor, and maintain them.Partner with engineering, analytics, AI/ML, and business teams to understand requirements and translate them into scalable technical solutions.Evaluate new technologies and capabilities that can expand the functionality and maturity of the data platform.Take ownership of complex technical problems and operate effectively in environments where requirements and solutions are not always fully defined.QualificationsSignificant experience in senior-level Data Engineering, Data Platform Engineering, or similar roles.Strong hands-on experience with Databricks, Spark/PySpark, SQL, cloud data architecture, data pipelines, and orchestration.Demonstrated experience building or significantly enhancing modern data platforms.Exposure to MLOps, ML/AI production environments, or deploying and supporting machine learning workloads is strongly preferred.Strong understanding of software engineering practices, architecture, scalability, governance, observability, and platform reliability.Experience working in greenfield, transformation, or highly ambiguous technical environments.Strong communication and collaboration skills with the ability to work effectively across technical and business teams.Self-directed mindset with the ability to understand business objectives and independently determine appropriate technical solutions.