At Ardent, we hire people who want more than a job — they want to serve a mission that matters. Our teams support the federal government’s most critical national security and defense priorities, helping protect the nation, strengthen resilience, and advance the technologies and capabilities that keep America secure. For veterans, cleared professionals, and purpose-driven innovators, Ardent is a place to continue serving alongside a team that understands the importance of the mission and the people behind it.
We also know top talent has choices, which is why we back our mission with benefits and flexibility that stand out: competitive pay, comprehensive health coverage, flexible PTO, federal holidays off, tuition reimbursement, professional development support, wellness stipends, and a culture that values and rewards hard work, dedication, and adaptability. If you want to build something meaningful, while enjoying the kind of flexibility and support that you need to do your best work — Ardent is where your next mission begins.
Ardent is seeking a Data Engineer to join our team.
This is a remote position.
Position Description:
Ardent is seeking a Data Engineer supporting the design, development, and maintenance of modern data engineering solutions that enable advanced analytics, reporting, and data-driven decision-making.
The successful candidate will design and maintain scalable data pipelines, integrate data from a variety of structured and unstructured sources, and optimize enterprise data platforms. The ideal candidate has experience working with modern data architectures, cloud-based data platforms, and enterprise data management practices while collaborating closely with technical teams and stakeholders to deliver reliable, high-quality data solutions.
Responsibilities and Duties:
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Data Engineering & Pipeline Development
- 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.
Data Platform Management
- 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.
Data Quality & Governance
- 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.
Collaboration & Analytics Support
- 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.
Requirements:
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- 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.
Ardent is an equal opportunity employer. We will not discriminate in employment, recruitment, advertisements for employment, compensation, termination, upgrading, promotions, and other conditions of employment against any employee or job applicant on the bases of race, color, gender, national origin, age, religion, creed, disability, veteran's status, sexual orientation, gender identity, gender expression, or any other basis protected by state, local, or federal law.
