Data Engineer / Metadata Engineer

Omniscius; Arlington (VA); On-site; USD 120,000 - 160,000; Full time

Job summary

Omniscius seeks a talented Data Engineer / Metadata Engineer to design, develop, and optimize data pipelines, metadata repositories, and governance solutions for enterprise analytics. You will ensure data quality, discoverability, lineage, cataloging, and integration across a complex data ecosystem.

The role blends strong data engineering with metadata management and governance frameworks and leverages modern cloud data platforms to support analytics, reporting, and data management initiatives.

Qualifications

• Bachelor’s degree or equivalent experience in a data-related field.
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• 3–7 years of experience in data engineering or metadata management.
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• Strong SQL development and data warehousing experience.
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• Understanding of metadata management, data lineage, and data catalogs.
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• Active TS clearance is required.

Responsibilities

• Design, build, and optimize data pipelines, metadata repositories, and data governance solutions.
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Skills

SQL development

Data warehousing

Data processing

Problem solving

Communication skills

Security clearance

Education

Bachelor's degree in CS/IS/Data Engineering or related

Tools

Microsoft Purview

Collibra

Alation

Informatica EDC

Apache Atlas

Azure

AWS

GCP

Job description

We are seeking a talented Data Engineer / Metadata Engineer to design, develop, and optimize data pipelines, metadata repositories, and data governance solutions that support enterprise analytics, reporting, and data management initiatives. This role will be responsible for ensuring data quality, discoverability, lineage, cataloging, and integration across a complex data ecosystem.

The ideal candidate combines strong technical data engineering skills with expertise in metadata management, data governance frameworks, and modern cloud data platforms.

Key Responsibilities

Data Engineering

• Design, build, and maintain scalable data pipelines and ETL/ELT processes.
• Integrate data from multiple structured and unstructured sources into enterprise data platforms.
• Integrate and correlate data sets both internal and external to customer organization.
• Develop and optimize data models, data warehouses, data lakes, and lakehouse architectures.
• Ensure data pipelines meet performance, reliability, and scalability requirements.
• Implement automation and monitoring for data ingestion and processing workflows.

Metadata Management

• Design and maintain enterprise metadata repositories and data catalogs.
• Define and manage business, technical, and operational metadata standards.
• Develop processes for automated metadata collection, classification, and enrichment.
• Maintain metadata lineage and impact analysis capabilities across data assets.
• Ensure metadata consistency and accuracy across enterprise systems.

Data Governance & Quality

• Support enterprise data governance initiatives and best practices.
• Partner with business and technical stakeholders to define data ownership and stewardship models.
• Implement data quality monitoring and validation controls.
• Ensure compliance with organizational data policies and regulatory requirements.
• Support master data management (MDM) and reference data initiatives.

Cloud & Platform Engineering

• Develop and support cloud-native data solutions within Azure, AWS, or Google Cloud environments.
• Build and optimize data integration solutions using cloud services and modern data tools.
• Support enterprise analytics, AI/ML, business intelligence workloads, and assist with build of automation-first pipelines.
• Contribute to infrastructure-as-code and data platform automation efforts.

Collaboration & Stakeholder Support

• Work closely with data architects, analysts, data scientists, governance teams, and business stakeholders.
• Translate business requirements into data engineering and metadata management solutions.
• Support data discovery, self-service analytics, and data literacy initiatives.
• Document system designs, data flows, metadata models, and operational procedures.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field, or equivalent experience.
• 3-7 years of experience in data engineering, metadata management, or related data platform roles.
• Experience building and maintaining ETL/ELT pipelines.
• Strong SQL development and database management skills.
• Experience with data warehousing and large-scale data processing.
• Understanding of metadata management, data lineage, and data catalog concepts.
• Strong problem-solving, analytical, and communication skills.
• Active Top Secret (TS) clearance

Preferred Qualifications

Experience with enterprise data catalog platforms such as:

• Microsoft Purview
• Collibra
• Alation
• Informatica EDC
• Apache Atlas

Experience with cloud platforms:

• Microsoft Azure
• AWS
• Google Cloud Platform

Familiarity with:

• Data Governance Frameworks
• Data Quality Management
• Master Data Management (MDM)
• Data Modeling
• Data Mesh and Data Fabric architectures

Additional Experience:

• Experience supporting AI, Machine Learning, and advanced analytics initiatives.