Responsibilities
- Develop and manage scalable data processing pipelines using Spark, Databricks, and cloud infrastructure
- Create data models tailored for analytical systems, machine learning, and artificial intelligence use cases
- Lead the integration of AI-powered tools and autonomous workflows within data engineering processes
- Discover and deploy AI-driven methods to enhance engineering productivity
- Experiment with and expand AI-supported development techniques
- Serve as the primary resource for AI testing and internal knowledge dissemination
- Support the creation of standards and participate in an AI-centered practice group
- Construct data pipelines that power machine learning models, large language model applications, and AI systems
- Maintain high standards for data accuracy, monitoring, and system dependability
- Work closely with Product, Data Science, ML/AI, and DevOps departments
