Senior Data Integration Operations Engineerr
About the Opportunity
Job Summary
Northeastern University is seeking an experienced and technically skilled Sr. Data Integration & Operations Engineer to join our team. This role is responsible for the day-to-day management, monitoring, operational support, and optimization of the university's data integration pipelines and processes. The role will oversee ETL/ELT workflows built on enterprise integration platforms, ensuring reliable data flow from a broad spectrum of university source systems into the data lakehouse and downstream point solutions used across the university. The position requires hands-on expertise in data integration platform administration, pipeline operations, data observability, incident management, and continuous improvement of integration processes in production environments.
24/7 business continuity:
This role requires availability outside of traditional working hours on a rotating basis to ensure continuous operation of critical AI systems and data pipelines. Responsibilities include monitoring system health, responding to alerts, troubleshooting performance issues, and implementing emergency fixes as needed. The ideal candidate must be able to quickly diagnose and resolve AI system and data pipeline incidents, prioritize issues based on business impact, and coordinate with technical teams to restore service. A strong commitment to system reliability and service continuity is essential for success in this position.
Other duties as required:
This role requires flexibility in performing duties outside of the primary responsibilities to support the evolving AI ecosystem at the university. The ideal candidate must be adaptable and willing to take on additional tasks or projects as required, ensuring consistent and reliable AI and data pipeline operations. This may include assisting with knowledge management, documentation updates, user training, data preparation, or special projects related to AI system improvements. A problem-solving mindset and willingness to tackle emerging challenges are essential for thriving in this dynamic environment.
Hybrid work schedule:
This role is hybrid and in the office a minimum of three days a week to facilitate collaboration with both technical teams and operations staff. In-office presence enables effective coordination with support teams, direct access to infrastructure, and hands-on troubleshooting of AI systems and data pipelines. Physical presence is particularly important for incident response, change management activities, and cross-functional problem-solving sessions that benefit from in-person collaboration and real-time communication.
Applicants must be authorized to work in the United States. The University is unable to work sponsor for this role, now or in the future.
Minimum Qualifications
- Data Integration Platform Experience: Hands-on experience administering and operating enterprise data integration platforms, with Informatica PowerCenter or IDMC (Intelligent Data Management Cloud) strongly preferred. Experience with SaaS-based ELT tools such as Fivetran is a plus.
- Data Pipeline Operations: Extensive experience maintaining, scheduling, and troubleshooting data integration pipelines that extract from enterprise source systems (ERP, SIS, CRM, HR, finance) and load into data lakehouse and downstream operational applications. Strong SQL/Python skills are required.
- Data Observability and Pipeline Monitoring: Experience with data observability platforms strongly preferred.
- Incident Management, Performance Optimization, Change Management, Data Quality Management, Documentation and Knowledge Management, Automation Skills, DevOps Practices, Security Awareness, Collaboration Skills, Problem-solving, Compliance Knowledge, Communication Skills, Service Management.
- Bachelor's degree in Computer Science, Information Technology, Data Management, or a related field.
- Minimum of 4-5 years of experience in data integration, data engineering operations, or a closely related IT operations role.
- Experience with cloud platforms (AWS, Azure, or GCP) and familiarity with cloud-based data lakehouse or data warehouse platforms.
Key Responsibilities & Accountabilities
Pipeline Monitoring, Observability, and Incident Management; Operational Support and Maintenance; Performance Analysis and Optimization; Documentation and Knowledge Management; Continuous Improvement and Automation.
Position Type: Information Technology
Compensation Grade/Pay Type: 114S
Expected Hiring Range: $130,945.00 - $189,868.75
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