Data Engineer / Metadata Engineer

ECS Federal•ARLINGTON, VA

3d•Hybrid

About The Position

Everforth ECS is seeking a Data Engineer / Metadata Engineer to support the Cybersecurity and Infrastructure Security Agency’s (CISA) Technical Engineering and Support Services (TESS) program. TESS is an integrated, capability-driven mission ecosystem supporting DHS, CISA, and the Cybersecurity Division. This role designs, develops, and optimizes data pipelines, metadata repositories, and data governance solutions for enterprise analytics, reporting, and data management. The position supports data quality, discoverability, lineage, cataloging, and integration across internal and external data sources. The ideal candidate combines data engineering expertise with metadata management, data governance, and modern cloud platform experience. The position follows a hybrid schedule in Everforth ECS’s Arlington, Virginia office.

Requirements

Active Top Secret (TS) security clearance.
Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field, or equivalent experience.
At least 5 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.

Responsibilities

Design, build, and maintain scalable data pipelines and ETL/ELT processes.
Integrate data from structured and unstructured sources into enterprise data platforms, and integrate and correlate datasets from internal and external sources.
Develop and optimize data models, data warehouses, data lakes, and lakehouse architectures.
Ensure pipelines meet performance, reliability, and scalability requirements; automate and monitor data ingestion and processing workflows.
Design and maintain enterprise metadata repositories and data catalogs.
Define and manage business, technical, and operational metadata standards.
Develop automated metadata collection, classification, and enrichment processes.
Maintain metadata lineage and impact analysis across data assets, and ensure metadata consistency and accuracy across enterprise systems.
Support enterprise data governance initiatives and best practices; partner with stakeholders to define data ownership and stewardship models.
Implement data quality monitoring and validation controls and 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 in Azure, AWS, or Google Cloud environments.
Build and optimize cloud-based data integration solutions and support analytics, AI/ML, and business intelligence workloads, including automation-first pipelines.
Contribute to infrastructure-as-code and data platform automation efforts.
Collaborate with data architects, analysts, data scientists, governance teams, and business stakeholders to translate business requirements into data engineering and metadata solutions.
Support data discovery, self-service analytics, and data literacy initiatives.
Document system designs, data flows, metadata models, and operational procedures.