AI & Data
Data Engineering
Designing and building systems that collect, store, and deliver data for analytics and ML.
Data engineering is the discipline of designing, building, and maintaining pipelines and infrastructure that ingest, transform, store, and serve data for analytics, machine learning, and applications. It includes data lakes, warehouses, ETL/ELT, streaming, and orchestration.
Technologies often include SQL and NoSQL databases, Apache Spark, Kafka, dbt, Airflow, and cloud services (e.g. BigQuery, Snowflake, Databricks). Reliable data engineering is essential for training ML models and running production AI systems. At Blue Note Logic we design data pipelines and architectures to support AI and analytics.