Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a related technical field (or equivalent combination of education and experience)
Minimum of 3 years of professional experience in data engineering or a related field
Demonstrated experience designing, building, and maintaining scalable ETL/ELT pipelines across multiple data sources
Strong proficiency in SQL and Python or equivalent technologies used for data engineering and transformation
Experience ingesting and transforming data from a variety of formats, including
Flat files
JSON
XML
Microsoft Excel
REST APIs
Graph databases
Additional structured and unstructured data sources
Experience working with Databricks Unity Catalog, SQL Server Managed Instances, or comparable enterprise data platforms
Experience with streaming and batch ingestion frameworks and modern Lakehouse architecture
Strong understanding of data quality, data lineage, performance optimization, and enterprise data management principles
Familiarity with data governance, data quality, and data management practices aligned with Enterprise Data Management (EDM) standards
Experience supporting fraud detection, anomaly detection, financial oversight analytics, or similar analytical environments is preferred
Excellent analytical, problem-solving, and communication skills with the ability to collaborate effectively across technical and business teams
Due to the nature of the work we support, all candidates selected for this position must be willing to undergo a U.S. Government background investigation
Due to the nature of the work we support, all candidates in consideration for this role must be willing to undergo the government issued background investigation process