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Senior Data Engineer

voyagertechnologiesinc

Remote - United States · senior
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Remote - United States
Location
Remote
Work arrangement
Senior
Seniority
voyagertechnologiesinc
Employer
Data Engineer jobs
Category

Voyager is an innovative space, defense, and national security technology company committed to advancing and delivering transformative, mission-critical solutions. We tackle the most complex challenges to unlock new frontiers for human progress, fortify national security, and protect critical assets to lead in the race for technological and operational superiority from ground to space.  Forge the Future: Join Voyager Technologies   The future belongs to those who build it.

At Voyager Technologies, we’re building technologies that protect lives, expand frontiers and prepare us for what’s next. And we’re doing that with people who are wired to solve, build, adapt and lead. These roles are not for the faint of heart.   You’ll help lay the foundation for humanity's future. Join a culture where innovation thrives, curiosity is rewarded, and impact is real. We’re a company of doers, thinkers and builders, united by purpose and grounded in reality.  If you want to put your skills to work where the stakes are real and the mission is bigger than any one person,  forge the future with Voyager.

  The Senior Data Engineer is responsible for designing and implementing the data workflows, integrations, and pipelines that connect enterprise manufacturing, ERP, PLM, MES, and quality systems into a cohesive, governed data ecosystem. This role is critical to enabling end-to-end traceability, operational visibility, and regulatory compliance across multi-site manufacturing operations. The ideal candidate brings deep experience integrating complex enterprise platforms in regulated manufacturing environments , is fluent in data engineering best practices, and can operate effectively across engineering, operations, IT, and compliance teams.

This is a senior individual contributor role with high organizational visibility and direct impact on production operations. This is a remote role based in the US and requires the ability to maintain or obtain a DOD clearance.  Key Responsibilities Enterprise System Integration Design, build, and maintain data integration workflows connecting MES, ERP, PLM, QMS, and supporting enterprise platforms.

Develop and own integration pipelines between systems such as Apriso (Delmia), NetSuite, ForProject, Empower, and 3DX PLM. Architect and implement API-based, event-driven, and batch integration patterns across cloud and on-premises manufacturing systems. Build and maintain data flows that support production execution, material management, traceability, scheduling, and quality processes. Partner with ERP, MES, and PLM implementation teams to design integration points, data contracts, and transformation logic ahead of go-live milestones.

Support multi-site rollout strategies by building reusable, configurable integration templates that can be replicated across facilities. Manufacturing Data Workflows & Traceability Design data workflows that support grain-level and sublot traceability across the full manufacturing lifecycle. Build pipelines that enforce compliance checkpoints including pot life hard stops, e-signature requirements, and hold point validations.

Integrate with LIMS systems to support quality data capture, lab result ingestion, and traceability linkage to production records. Support automated generation of regulatory document packages (travelers, WARPs, and production records) through structured data workflows. Develop integrations with PLC/SCADA and automated traceability systems where applicable. Data Pipeline Development & Architecture Build and maintain scalable ELT/ETL pipelines for operational, analytical, and compliance reporting workloads.

Architect data flows from source systems through transformation and serving layers with full lineage, observability, and auditability. Implement data quality frameworks including validation rules, anomaly detection, and SLA monitoring across all pipeline stages. Define data models, naming conventions, and integration standard

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