Data Engineer (Job ID:4342)

Valkyrie•Virginia Beach, VA

21h•$90,000 - $120,000•Hybrid

About The Position

Valkyrie Enterprises has need for a Data Engineer in Virginia Beach, VA. This role is Hybrid. The Data Engineer supports Valkyrie’s Data & AI initiatives by designing, building, and maintaining reliable enterprise data pipelines, integrations, and curated datasets that enable reporting, automation, analytics, and future AI-enabled capabilities. This role is responsible for helping establish and scale the organization’s enterprise data foundation by transforming raw operational data into trusted, structured, and reusable data assets. The Data Engineer works across enterprise systems, data platforms, and operational workflows to improve data accessibility, reliability, and consistency throughout the organization. The role focuses on developing scalable data pipelines, supporting enterprise reporting and planning needs, improving data quality and observability, and preparing data structures that support automation and AI initiatives. This position works closely with IT Services and stakeholders across the enterprise to support the successful delivery, expansion, and ongoing improvement of enterprise data capabilities.

Requirements

Must have a bachelor’s degree in Information Systems, Computer Science, Engineering, Data Analytics, or a related field and at least 5 years of relevant professional experience, or an equivalent combination of education and experience.
Must have hands-on experience developing and supporting ETL/ELT pipelines, data integrations, or enterprise data solutions.
Must demonstrate strong SQL and Python skills in production or enterprise environments.
Must have experience supporting modern data warehouse or cloud-based data platforms.
Must demonstrate experience working with structured and unstructured data sources across enterprise systems.
Must demonstrate the ability to troubleshoot data quality, integration, and pipeline performance issues.
Must possess strong written and verbal communication skills and the ability to work effectively across technical and non-technical teams.
Must demonstrates foundational ability to translate business and operational requirements into technical solutions.
Must be capable of working independently with appropriate guidance, exercising sound judgement and contributing to multiple concurrent initiatives.
Must have the ability to obtain a U.S. Government security clearance.
Must comply with all Valkyrie Enterprises security policies and procedures.

Nice To Haves

Experience with cloud data platforms and services such as Snowflake and Azure, preferred.
Experience supporting reporting, analytics, automation, or AI-enabled business initiatives, preferred.
Experience working with ERP, HRIS, finance, workforce, or operational business systems, preferred.
Familiarity with orchestration, monitoring, observability, or data validation frameworks, preferred.
Experience supporting machine learning, intelligent automation, or AI-related data preparation workflows, preferred.
Experience working in a defense contractor, government, or regulated compliance environment, preferred.
Experience with version control, testing, and deployment practices for data pipelines, preferred.

Responsibilities

Develop and maintain scalable ETL/ELT pipelines across enterprise systems and operational data sources.
Build and maintain curated datasets that support reporting, planning, analytics, automation, and AI initiatives.
Design and support enterprise data warehouse models and data integration workflows.
Improve data quality, validation, monitoring, lineage, and operational reliability across the data platform.
Support ingestion and integration of new enterprise systems, business applications, and operational data sources.
Troubleshoot pipeline failures, performance issues, and data inconsistencies while driving root-cause resolution.
Support AI and automation initiatives by preparing structured, reusable, and model-ready datasets.
Partner with stakeholders to translate operational and reporting needs into scalable technical solutions.
Contribute to engineering standards, documentation, deployment practices, and operational support procedures.
Collaborate with technical leadership and product stakeholders on backlog priorities, sequencing, and delivery planning.