Senior Data & Metadata Engineer – Hybrid (Arlington)

ECS Corporate Services; Arlington (VA); Hybrid; USD 160,000 - 180,000; Full time

Benefits offered by this job

Top Secret clearance

Job summary

Everforth ECS in Arlington, VA (Hybrid) is seeking a Data/Metadata Engineer to design, develop, and optimize data pipelines, metadata repositories, and data governance solutions that support analytics and data management initiatives. This role focuses on data quality, discoverability, lineage, cataloging, and integration across a complex data ecosystem.

Responsibilities include building scalable ETL/ELT pipelines, integrating diverse data sources, designing data models and lakehouse

Qualifications

• Bachelor's degree or equivalent experience in CS/IS/Data Engineering.
• 7+ years of experience in data engineering, metadata management, or related data platform roles.
• Experience building ETL/ELT pipelines; strong SQL and data warehousing knowledge.

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT processes.
• Integrate data from structured and unstructured sources into enterprise data platforms.
• Develop and optimize data models, warehouses, lakes, and lakehouse architectures.
• Ensure data quality, lineage, cataloging, and governance across assets.
• Build cloud-native data solutions in Azure, AWS, or Google Cloud.
• Collaborate with data architects, analysts, and governance teams to translate requirements.

Skills

SQL development

Data engineering

Communication skills

Problem-solving

Education

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field

Tools

Azure

AWS

Google Cloud

Data warehousing tools

Metadata management tools

Job description

Everforth ECS in Arlington, VA (Hybrid) is seeking a Data/Metadata Engineer to design, develop, and optimize data pipelines, metadata repositories, and data governance solutions that support analytics and data management initiatives. This role focuses on data quality, discoverability, lineage, cataloging, and integration across a complex data ecosystem.

Responsibilities include building scalable ETL/ELT pipelines, integrating diverse data sources, designing data models and lakehouse