Data Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Ardent

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2008

🤖 Artificial Intelligence

🔒 Cybersecurity

🏛️ Government

Artificial Intelligence • Cybersecurity • Government

Ardent is a premier technology firm serving the public sector, focused on delivering mission-critical solutions. They specialize in data science and analytics, digital transformation, and location intelligence, helping organizations to make better decisions, modernize their systems, and decode spatial data. Ardent is committed to defending against man-made and natural threats, providing effective solutions such as cloud applications, cybersecurity, and spatial data science. They work closely with federal agencies, including the Department of Homeland Security, to ensure national safety. Their solutions are tailored to thrive in complex environments, proven in case studies, and delivered with the speed and precision required by their clients' missions.

📋 Description

• 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.

🎯 Requirements

• 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. • Must be willing to undergo a U.S. Government background investigation.

🏖️ Benefits

• competitive pay • comprehensive health coverage • flexible PTO • federal holidays off • tuition reimbursement • professional development support • wellness stipends • culture that values and rewards hard work, dedication, and adaptability