Data Engineer

What we need to see: Strong SQL skills, including advanced SQL concepts such as window functions, CTEs, complex joins, aggregation patterns, query optimization, and analytical query design. Strong Python skills, or equivalent experience building data-intensive software systems. Experience designing data models, analytics datasets, data products, or application data layers. Experience building or owning production data pipelines, data platforms, or analytics systems. Strong understanding of data correctness, table grain, lineage, metric definitions, validation rules, and data quality standards. Ability to learn complex technical domains and identify when data outputs are technically valid but semantically wrong. Ability to work multi-functionally with domain experts, engineers, product/UI teams, and data engineering teams while providing technical ownership and judgment. Interest in applied AI/ML and how trusted data foundations enable AI-based exploration, anomaly detection, predictive analytics, and recommendations. Bachelor's or Master's degree in Computer Science or Computer Engineering or Electrical Engineering (or equivalent experience) and 8+ years of relevant experience Ways to stand out from the crowd: Experience with semiconductor product engineering, test engineering, yield analytics, manufacturing analytics, quality, reliability, or hardware engineering data is a strong plus! Experience with modern cloud data platforms, data lake, or lakehouse technologies such as S3, Athena, Glue, Redshift, EMR, Spark, Databricks, Delta Lake, or similar technologies. Experience with AI/ML-enabled analytics, including LLMs, RAG, AI-based data exploration, natural-language-to-SQL, feature engineering, anomaly detection, prediction, or recommendation systems. Experience building engineering analytics platforms, internal data products, or decision-support tools for technical users. #J-18808-Ljbffr