We are looking for a Software Engineer to join a Contract engagement in Cambridge, Massachusetts within the IT Software industry. This role is well suited for a senior engineer who can take ownership of a backup and recovery initiative, bringing a delayed implementation to completion with minimal oversight. The position will focus on strengthening infrastructure resilience through hands-on Acronis deployment, system configuration, and issue resolution across a virtualized server environment.<br><br>Responsibilities:<br>• Lead the completion of an enterprise backup deployment project and move the initiative through final implementation stages.<br>• Configure and administer Acronis backup solutions across approximately 150 virtual machines in a VMware-based environment.<br>• Install and validate backup agents on targeted systems to ensure reliable protection coverage.<br>• Diagnose and resolve configuration, connectivity, and performance issues affecting backup operations.<br>• Improve disaster recovery readiness by aligning backup processes with infrastructure protection goals.<br>• Work independently to plan tasks, manage technical priorities, and deliver project milestones with limited supervision.<br>• Support backup operations across Windows Server and Linux/Red Hat environments, ensuring compatibility and stability.
We are looking for a Data Engineer to support enterprise data movement and application integration efforts in Boston, Massachusetts. This Long-term Contract position will focus on building, maintaining, and enhancing custom services that transfer, load, and transform data across multiple systems. The role works closely with technical and business teams to deliver reliable integration solutions using .NET/C#, APIs, and modern deployment practices.<br><br>Responsibilities:<br>• Design, support, and improve custom integration services that move data between enterprise platforms and applications.<br>• Build and maintain ETL processes for data loading, transformation, and system-to-system exchange.<br>• Develop microservice-based solutions in .NET/C# to replace larger legacy integration components where needed.<br>• Create and support API-driven integrations, including services that rely on REST and SOAP protocols.<br>• Partner with business analysts, developers, and solution stakeholders to translate operational needs into technical data workflows.<br>• Monitor data pipelines and integration jobs, troubleshoot failures, and resolve performance or reliability issues.<br>• Contribute to deployment and release activities using Azure DevOps or comparable CI/CD tools.<br>• Support integrations involving key enterprise platforms such as Salesforce and higher education systems when applicable.
We are looking for a Data Engineer to join a hybrid team in Massachusetts in a contract capacity with the potential to become permanent. This role focuses on designing dependable data solutions that support reporting, analytics, and broader business needs. The ideal candidate brings hands-on experience with modern cloud data platforms and enjoys improving data flow, structure, and performance across production environments.<br><br>Responsibilities:<br>• Design, build, and enhance scalable data pipelines that support reliable movement and transformation of enterprise data.<br>• Create and refine Snowflake data models to ensure efficient storage, accessibility, and performance for downstream use.<br>• Bring new internal and external data sources into existing workflows while maintaining consistency and integrity across systems.<br>• Track pipeline health, investigate processing issues, and resolve data anomalies to keep production operations stable.<br>• Strengthen data workflows through automation, process optimization, and improved operational efficiency.<br>• Work closely with analysts, architects, software engineers, and business partners to deliver dependable data solutions aligned with organizational goals.<br>• Produce clear technical documentation covering pipeline logic, data processes, and engineering standards.<br>• Apply data quality checks, validation methods, and error-handling practices to support trustworthy and governed datasets.