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Ardent

Data Engineer

Ardent

Data Engineer developing and maintaining data engineering solutions for national security priorities support at Ardent. Designing scalable ETL/ELT pipelines and collaborating with technical teams.

Posted 7/2/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and maintaining scalable ETL/ELT pipelines, utilizing SQL and Python for data processing, and implementing data quality controls aligned with enterprise data management standards. Proficient in modern data platforms like Databricks Unity Catalog and SQL Server Managed Instances, with a strong focus on data governance and performance optimization.

Highest-signal resume keywords
ETL/ELT Pipeline DevelopmentSQL ProficiencyPython ProgrammingDatabricks Unity CatalogData Quality Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
ETL/ELT Pipeline DevelopmentSQL ProficiencyPython ProgrammingData TransformationData Quality ControlData Lineage ManagementPerformance OptimizationData GovernanceBatch Ingestion FrameworksStreaming Ingestion Frameworks
Soft Skills
Analytical SkillsProblem-Solving SkillsCommunication SkillsCollaboration Skills
Tools & Technologies
Databricks Unity CatalogSQL Server Managed InstancesREST APIsGraph DatabasesMicrosoft Excel
Industry Keywords
Enterprise Data ManagementData GovernanceData QualityFraud DetectionAnomaly Detection

Tech Stack

Tools & technologies
ETLPythonSQLUnity

About the role

Key responsibilities & impact
  • 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

What you’ll need
  • 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

Comp & perks
  • 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