Lakehouse Engineer and Analyst, Mid

What you'll do

• Build and maintain a modern Databricks Lakehouse environment for real-time fraud detection and risk insights.
• Develop data pipelines using PySpark, Delta Lake, and medallion architecture to process structured and unstructured data.
• Implement Unity Catalog governance and access controls within the Databricks platform.
• Integrate machine learning models and natural language processing techniques into production workflows.
• Perform text mining and advanced analytics to support fraud investigation and risk scoring.
• Manage structured streaming data to enable real-time investigative analytics.
• Coordinate with technical and non-technical stakeholders to align data capabilities with fraud operations needs.

What we're looking for

• 3+ years of experience in data engineering, analytics engineering, or ML engineering.
• Experience with Databricks, Delta Lake, PySpark, structured streaming, and medallion architecture.
• Knowledge of Unity Catalog governance, access controls, text mining, and ML techniques.
• Experience supporting fraud analytics, risk scoring, or anomaly detection.
• 2+ years of experience in developing algorithms using R, Python, SQL, or NoSQL (preferred).
• 2+ years of experience with distributed data tools like Hadoop, Hive, Kafka, or Spark (preferred).
• Bachelor’s degree.