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3 results for Engineer in Greenville, SC

Network Engineer

Greenville, SC
onsite
Temporary / Contract
45 - 52 USD / Hourly
This role centers on network architecture, design, and high‑level engineering for an enterprise environment. The Network Engineer will shape the organization’s network design and infrastructure architecture while providing limited hands‑on implementation support. The position ensures the reliability, performance, and security of both corporate and SCADA network environments, with responsibility for long‑term planning, standards development, and Tier 3 escalation.Key Responsibilities<ul><li>Lead the design of LAN/WAN architectures, including planning, documentation, and future‑state network strategy.</li><li>Develop and maintain enterprise routing, switching, and security standards across core network platforms.</li><li>Oversee SCADA network architecture, ensuring secure and reliable connectivity between operational and corporate systems.</li><li>Evaluate emerging technologies and recommend improvements to enhance performance, resilience, and security.</li><li>Monitor network health and performance, performing advanced troubleshooting and root‑cause analysis as needed.</li><li>Produce and maintain network documentation, diagrams, and configuration standards.</li><li>Provide Tier 3 support for complex network issues and participate in after‑hours incident response when required.</li></ul>
2026-05-04T00:00:00Z

Data Engineer

Greer, SC
onsite
Temporary to Hire
64.6 - 74.8 USD / Hourly
We are looking for a Data Engineer to join a financial services organization in Greer, South Carolina on a contract-to-permanent basis. This role focuses on building and enhancing modern data pipelines within a cloud-centered environment, with Snowflake serving as the primary data platform. The ideal candidate will help deliver production-ready solutions, strengthen data reliability, and apply disciplined engineering practices to support scalable, near real-time data processing. Responsibilities: • Design, build, and deliver end-to-end data pipelines in Snowflake that support business reporting and data consumption needs. • Create new ingestion and transformation workflows while troubleshooting pipeline issues to improve stability and performance. • Contribute to a delivery model that balances new development with targeted optimization of existing data assets and workflows. • Implement streaming and event-driven ingestion patterns using Kafka to support timely and scalable data movement. • Improve observability across the data ecosystem by strengthening monitoring, alerting, and data quality controls. • Help simplify legacy data processes by reducing technical debt and modernizing outdated pipeline components. • Apply sound software engineering standards, including maintainable code, documentation, and repeatable development practices. • Support the advancement of testing and CI/CD processes by helping establish more consistent engineering workflows. • Leverage AI-assisted development tools to accelerate coding, validation, and technical documentation where appropriate.
2026-05-22T00:00:00Z

Data Engineer

Greer, SC
onsite
Temporary to Hire
64.6 - 74.8 USD / Hourly
We are looking for a Data Engineer to join a financial services organization in Greer, South Carolina on a contract basis with the potential for a permanent role. This role focuses on designing and delivering modern data pipelines in a cloud-based environment, with an emphasis on reliability, quality, and scalable data processing. The position offers the opportunity to contribute to both new development and targeted improvements across an evolving data ecosystem centered on Snowflake and event-driven ingestion. Responsibilities: • Design, build, and deliver end-to-end data pipelines in Snowflake to support business and analytics needs. • Create new data integration workflows while troubleshooting and resolving issues in existing pipelines. • Apply sound engineering practices for coding, documentation, testing, and deployment to improve consistency and maintainability. • Balance hands-on development of new solutions with optimization work that improves performance, stability, and efficiency. • Develop streaming and ingestion processes using Kafka to enable timely and dependable data movement. • Strengthen observability and data quality controls so pipeline health and accuracy are easier to monitor and maintain. • Help reduce technical debt by simplifying legacy data processes and modernizing pipeline design where appropriate. • Contribute to AI-assisted engineering efforts by using approved tools to accelerate development, testing, and documentation activities.
2026-05-22T00:00:00Z