CyrusOne's Customer Telemetry program delivers real-time Electrical Power Management System (EPMS) and Building Management System (BMS) data to hyperscale customers. As customer demand and telemetry complexity continue to grow, CyrusOne is seeking a Data Engineer to help develop scalable data solutions that improve the delivery, accessibility, and use of telemetry data across the organization.
This role combines data engineering, telemetry data management, and emerging AI technologies. The Data Engineer will build and maintain data pipelines, ensure telemetry data quality and delivery, and support the development of AI-enabled solutions that leverage telemetry and operational data. The position will work closely with telemetry, operations, controls, commissioning, analytics, and customer teams to improve both customer-facing and internal data capabilities.
The ideal candidate has a strong foundation in Python, SQL, cloud-based data platforms, and modern data engineering practices, along with exposure to Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) solutions, or other AI-enabled applications
Essential Functions & ResponsibilitiesAI & Advanced Analytics Solutions- Support the development and implementation of AI-enabled solutions utilizing Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) platforms, and related technologies.
- Partner with business and technical stakeholders to identify opportunities where AI can improve telemetry data accessibility, operational insights, and customer experiences.
- Evaluate emerging AI approaches, including agent-based and multi-agent systems, for applicable business use cases.
- Assist in developing, testing, and deploying AI-powered tools and applications.
Data Engineering & Pipeline Development- Design, develop, and maintain scalable data pipelines that ingest, transform, validate, and distribute telemetry data.
- Build and optimize data models that support reporting, analytics, and AI-enabled solutions.
- Develop automated processes to monitor data quality, integrity, and reliability.
- Support cloud-based data architecture and integration efforts.
Telemetry Data Management- Ensure accurate mapping, validation, and delivery of EPMS and BMS telemetry data.
- Develop repeatable ingestion and validation processes that improve consistency and reduce delivery timelines.
- Troubleshoot data quality issues, mapping discrepancies, and telemetry integration challenges.
- Support telemetry onboarding activities for new customers and facilities.
Customer & Cross-Functional Collaboration- Partner with customer technical teams to understand telemetry requirements and support data validation efforts.
- Participate in troubleshooting activities related to telemetry delivery and data quality concerns.
- Collaborate with Controls, Construction, Commissioning, Operations, and Analytics teams to support ongoing telemetry initiatives.
Documentation & Continuous Improvement- Maintain documentation for data pipelines, system configurations, telemetry mappings, and AI-enabled solutions.
- Identify opportunities to improve processes, automation, and scalability.
- Contribute to the development of best practices for telemetry data management and AI solution delivery.
Qualifications- 1-3 years of relevant experience in data engineering, data analytics, AI-enabled applications, or related technical disciplines.
- Experience using Python and SQL for data engineering, automation, or data analysis.
- Familiarity with cloud-based data platforms and data architectures.
- Experience developing or supporting data pipelines and data integration solutions.
- Familiarity with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) platforms, or similar AI technologies.
- Strong analytical and problem-solving skills.
- Strong communication and collaboration skills.
- Ability to manage multiple priorities in a fast-paced environment.
Preferred- Experience working with telemetry, IoT, OT, SCADA, EPMS, BMS, or similar operational data environments.
- Experience supporting AI-enabled applications or solutions in a production environment.
- Familiarity with multi-agent systems or agent-based AI frameworks.
- Experience supporting customer-facing technical solutions.
- Experience within data center, mission-critical facility, industrial, or infrastructure environments.
- Knowledge of telemetry protocols such as BACnet, Modbus, MQTT, or similar technologies.
Education - Bachelor's degree in Computer Science, Data Engineering, Electrical Engineering, Data Science, Artificial Intelligence, or a related technical field, or equivalent practical experience.
