ML Engineer / ML Data Engineer

ML Engineer / ML Data Engineer Charlotte, NC 12 Months MUST HAVE • 8+ years of experience • Strong Python • Strong Spark / PySpark • Databricks (must have) • Feature Engineering experience • Building ML data pipelines • Data Ingestion and ETL/ELT development • Cloud • Experience supporting ML/AI initiatives WHAT THEY SHOULD HAVE DONE Candidates should be able to explain: Data Ingestion • Built pipelines from databases, APIs, Kafka, files, etc. • Processed large-scale datasets Feature Engineering • Created ML features from raw data • Built reusable feature pipelines • Worked with Feature Stores Examples: • Customer behavioral features • Fraud detection features • Risk scoring features • Recommendation engine features Production ML Support • Supported Data Scientists • Delivered features for model training/inference • Optimized feature pipelines • Maintained production ML datasets Databricks / Spark • PySpark transformations • Delta Lake • Databricks Workflows • Production ETL pipelines NICE TO HAVE • MLflow • Feature Store • MLOps • Model Monitoring • Kubernetes • Airflow • Kafka