Data Engineer / Metadata Engineer

Omniscius Consulting is seeking a Data Engineer / Metadata Engineer to support enterprise analytics and data management efforts from an Arlington, VA onsite location. In this role, you will design and optimize data pipelines alongside the metadata repositories and governance capabilities that enable discovery, lineage, cataloging, and reliable decision-making.

Role Summary

You will be responsible for building and maintaining scalable data engineering solutions, including ETL/ELT processes, data integration, and cloud-native platform components. A key focus is creating and sustaining metadata management systems that improve data quality, discoverability, and consistency across enterprise environments.

Responsibilities

• 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 datasets both internal and external to the 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.
• 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.
• 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.
• 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 automation-first pipelines.
• Contribute to infrastructure-as-code and data platform automation efforts.
• 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.

Requirements

• 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.

Technologies

• SQL; ETL/ELT
• Azure, AWS, Google Cloud
• Microsoft Purview; Collibra; Alation; Informatica EDC; Apache Atlas
• Data Governance Frameworks; Data Quality Management; Master Data Management (MDM)
• Data Modeling; Data Mesh and Data Fabric

Preferred Qualifications

• Experience with enterprise data catalog platforms such as Microsoft Purview.
• Experience with enterprise data catalog platforms such as Collibra.
• Experience with enterprise data catalog platforms such as Alation.
• Experience with enterprise data catalog platforms such as Informatica EDC.
• Experience with enterprise data catalog platforms such as Apache Atlas.
• Experience with cloud platforms: Microsoft Azure.
• Experience with cloud platforms: AWS.
• Experience with cloud platforms: Google Cloud Platform.
• Familiarity with Data Governance Frameworks.
• Familiarity with Data Quality Management.
• Familiarity with Master Data Management (MDM).
• Familiarity with Data Modeling.
• Familiarity with Data Mesh and Data Fabric architectures.
• Experience supporting AI, Machine Learning, and advanced analytics initiatives.

Location: Arlington, VA (onsite) | Experience: 3+ years