Must haves 4+ years of experience in production-level data engineering or similar roles Deep proficiency in SQL and Python Proven track record of owning and scaling production-grade data pipelines, including versioning, testing, and monitoring Strong understanding of data modeling, normalization/denormalization trade-offs, and data quality management Experience with the modern data stack: DBT, Databricks, Spark, Delta Lake Strong analytical skills – ability to design and evaluate data-driven hypotheses and KPIs Product and business awareness – you think about the impact of what you build, not just the implementation Preferred Qualifications Experience with GenAI and LLM applications — particularly extracting structure from unstructured data at scale Experience working with external data sources and vendors Familiarity with Unity Catalog and data governance at scale Familiarity with Terraform or similar infrastructure-as-code tools Experience with cost optimization on Databricks (DBU analysis, cluster policies) Familiarity with cloud-native platforms (AWS preferred) BSc/BA in Computer Science, Engineering, or a related technical field — or graduation from a top-tier IDF tech unit
