Note: The job is a remote job and is open to candidates in USA. Ardent is a company focused on supporting the federal government's national security and defense priorities. They are seeking a Data Engineer to design, develop, and maintain data engineering solutions that enable advanced analytics and data-driven decision-making.
Responsibilities
- Design, develop, and maintain scalable ETL/ELT pipelines to support enterprise data integration and analytics
- Ingest, transform, and integrate data from diverse sources, including flat files, JSON, XML, Excel, REST APIs, graph databases, and other structured and unstructured data formats
- Develop and optimize SQL and Python-based data processing solutions to support efficient data ingestion and transformation
- Build and maintain reusable, scalable data workflows that support business intelligence, reporting, and advanced analytics
- Load, manage, and optimize data within modern data platforms, including Databricks Unity Catalog and SQL Server Managed Instances
- Support both batch and streaming data ingestion frameworks
- Implement and maintain modern Lakehouse architecture solutions to improve scalability, performance, and accessibility
- Monitor and optimize database and pipeline performance to ensure efficient processing and storage
- Implement data quality controls to ensure the accuracy, consistency, reliability, and integrity of enterprise data
- Maintain data lineage and metadata to support governance and regulatory compliance
- Apply enterprise data management (EDM) standards and best practices throughout the data lifecycle
- Support data governance initiatives, including documentation, validation, and quality assurance activities
- Collaborate with cross-functional teams, including data analysts, software developers, architects, and business stakeholders, to understand data requirements and deliver effective solutions
- Support analytical environments focused on fraud detection, anomaly detection, financial oversight, and other data-driven initiatives
- Troubleshoot and resolve data pipeline, integration, and performance issues while continuously improving existing processes
Skills
- 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
- 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
- Experience supporting fraud detection, anomaly detection, financial oversight analytics, or similar analytical environments
Benefits
- Competitive pay
- Comprehensive health coverage
- Flexible PTO
- Federal holidays off
- Tuition reimbursement
- Professional development support
- Wellness stipends
- A culture that values and rewards hard work, dedication, and adaptability
Company Overview