The Manager, Data Operations will lead a team that is responsible for the reliability, performance, and scalability of our Databricks-based data platform. In this role, you will own the platform's operational health, lead and direct the team, set technical direction, and partner closely with cross-functional stakeholders and Engineering teams to ensure our data pipelines and infrastructure consistently deliver for the business.

This is a people-leadership role that requires strong technical fluency — you should be comfortable going deep with your engineers when needed while keeping the broader operational picture in focus. Excellent communication, organizational, and prioritization skills are essential.

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.

Required or Preferred Qualifications (specify within):

• 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

Essential Competencies:

• 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.

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