Data Engineer

• At least three (3) years of professional experience in data engineering or a related field.
• Pipeline Engineering: Demonstrated ability to design, build, and maintain scalable ETL pipelines across diverse data sources.
• Data Management Standards: Familiarity with data governance, data quality, and data management practices consistent with Enterprise Data Management (EDM) standards.
• Languages & Ingestion: Strong SQL and Python skills (or equivalent) to ingest and transform data from flat files, JSON, XML, Excel, APIs, and graph databases, with flexibility to adapt to new formats.
• Platforms & Architecture: Hands-on experience loading, managing, and optimizing data within Databricks Unity Catalog and SQL Server managed instances. Proficient with streaming/batch ingestion frameworks and modern Lakehouse architecture.
• Quality Control: Proven capability in implementing standard processes to ensure data quality, lineage, reliability, and performance while collaborating with cross-functional teams.

Preferred Requirements:

• Experience supporting a fraud detection, anomaly detection, or financial oversight analytics environment.

Physical Requirements:

• The person in this position must be able to remain in a stationary position 50% of the time. Occasionally move about inside the office to access file cabinets, office machinery, or to communicate with co-workers, management, and customers, via email, phone, and or virtual communication, which may involve delivering presentations.