• Python, data structures, basic software engineering discipline (clean code, testing) • ML fundamentals: supervised/unsupervised learning, metrics, bias/variance, evaluation • Data handling: SQL, data quality, feature understanding • Git, basic CI/CD awareness • Cloud basics (any of AWS/Azure/GCP), containers (Docker) basics • Distributed computing: Spark, Ray • Data engineering familiarity: ETL/ELT, orchestration (Airflow/ADF) • Security basics: secrets management, IAM concepts