Responsibilities Partner with AI/ML product teams to proactively identify data needs for rapid experimentation and stable production deployment. Ensure data availability by collaborating with Product teams. Support Data Analysts, Data Scientists, MLOps engineers in developing optimized data models, pipelines and frameworks. Build pipelines to ingest, clean, and transform structured, semi-structured, and unstructured data formats. Conduct data profiling, validation, and anomaly detection. Build vector databases for semantic search and retrieval of unstructured content. Collaborate with data scientists and ML engineers to design end-to-end generative AI solutions. Build clean, error-free MVP ready data models. Requirements 5 years of experience that includes ETL/ELT workflow experience in design, configuration, data mapping, extraction, transformation and loading. Writing code and maintaining it. Data warehousing high-level principles and understanding of business intelligence. Experience working with Databricks and Apache Spark/Py Spark. Proficiency with complex SQL development. Fluent in English. #J-18808-Ljbffr