OneOncology is a company focused on transforming medical care for cancer patients through a technology-driven, patient-centric approach. The Manager, Data Engineering Operations will lead a team responsible for the operational health of the data platform, ensuring reliability and performance while collaborating with cross-functional stakeholders.
Responsibilities:
- Lead, mentor, and develop engineers on the Data Operations team, including hiring, performance management, and career development as needed
- Set clear goals, deliver regular feedback, and create growth opportunities for each team member
- Foster a collaborative, high-accountability team culture focused on quality, continuous improvement, and operational efficiency
- Manage team capacity, workload, and prioritization across competing demands
- Own incident management and resolution for pipeline failures, cluster issues, and data quality problems, driving thorough root cause analysis and lasting preventative improvements
- Define and enforce operational standards, runbooks, and on-call practices for the team
- Manage and maintain Databricks Workflows and job orchestration, ensuring SLAs are consistently met
- Establish and report on operational KPIs (uptime, pipeline reliability, incident response, cost) to leadership and stakeholders
- Set technical direction for the data platform in partnership with senior engineering leadership
- Drive platform reliability, performance, and cost-efficiency initiatives
- Partner with IT, Security, and Engineering teams on platform architecture, governance, and integration decisions
- Champion engineering best practices including code review, testing, observability, and documentation
- Serve as the primary point of contact for data platform operations across the business
- Communicate operational status, risks, and roadmap clearly to both technical and non-technical audiences
- Build strong working relationships with downstream consumers, ensuring the platform meets their needs
- Additional responsibilities as assigned to help drive our mission of improving the lives of everyone living with cancer
Requirements:
- 8+ years of hands-on data engineering experience, with at least 2 years in a leadership or management role
- Strong hands-on background with SQL development and relational/non-relational databases, including data modeling, schema design, and query optimization
- Professional experience developing scalable solutions in Python or a similar object-oriented language
- Proficiency in Databricks, Spark, and Delta tables; experience operating large-scale distributed data processing in production
- Demonstrated experience operating and monitoring data pipelines at scale, including incident response and on-call leadership
- Solid understanding of Lakehouse and Medallion architectures
- Experience with Azure data services (ADLS Gen2, Azure Data Factory, Event Hubs, or equivalent)
- Familiarity with Unity Catalog for data governance, access control, and data lineage
- Proven experience designing and maintaining data integration/ETL pipelines using Azure Data Factory or equivalent
- Excellent communication and organizational skills, with a track record of conveying technical concepts and operational status to diverse audiences
- Ability to drive alignment and influence decisions across cross-functional stakeholders
- Experience hiring, developing, and retaining engineering talent
- Strong operational ownership mindset with a focus on reliability, scalability, and continuous improvement
- Leadership ability to set technical direction while balancing business priorities and team execution
- Effective decision-making and prioritization in fast-paced, production-focused environments
- Attendance is an essential job function