Sr Manager, Data Engineering

Position Overview 

The Sr. Manager, Data Engineering is the Enterprise Data department's accountable engineering leader for a specified data domain, owning domain data engineering strategy, delivery, data quality practices, stakeholder alignment, technical governance, and the integrated roadmap for business-critical capabilities. The role aligns domain data products and integrations to shared platform capabilities and represents the domain in platform direction and decisions. 

The role leads the domain data engineering organization, including domain Staff Engineers, and holds full people accountability for that organization. Where delivery depends on shared or matrixed teams, the role partners with their accountable leaders to execute domain priorities. 

The Sr. Manager is accountable for timely resolution of material technical decisions within delegated domain boundaries and owns priority, delivery, and technical-debt tradeoffs. Staff Engineers own domain technical design, solutioning, and recommendations, with support of Principal Engineers who provide cross-domain standards and technical guidance. The role represents Enterprise Data in cross-functional forums and partners with Software Engineering, IT Applications, Security, Privacy, Enterprise Architecture, and the AI organization to maintain a unified, well-governed data architecture. 

This role is based in Madison, WI.

Essential Duties 

Include, but are not limited to, the following: 

Domain accountability and delivery 

• Own domain data engineering strategy, prioritization, the integrated roadmap, delivery planning, cross-system integration, risks, and stakeholder outcomes for the domain. 

• Lead the domain data engineering organization to deliver required outcomes on schedule and ensure data quality practices follow enterprise standards, established patterns, and agreed technical direction. 

• Engage domain business leadership to shape priorities, set direction, and align on outcomes and delivery commitments. 

• Partner with the leaders of dependent or shared teams on execution, escalating capacity, sequencing, and dependency conflicts as needed. 

Technical decision-making and architecture 

• Ensure timely resolution of material technical decisions within delegated domain boundaries. Staff Engineers own technical design and recommendations; the Sr. Manager owns priority, delivery, and technical-debt tradeoffs. 

• Govern the domain integration approach, including authoritative data sources, systems of record, API, event, and batch patterns, data contracts and schemas, and where applicable, entity resolution across domain records. 

• Require adoption of enterprise Data Engineering standards and shared capabilities, maintain a secure architecture, and ensure domain data products are documented, discoverable, governed, observable, and supported throughout their lifecycle for governed reuse across analytics, semantic layers, machine learning, and AI applications. 

• Partner with Software Engineering, IT Applications, Security, Privacy, Enterprise Architecture, and the AI organization to align integration strategies and platform direction. 

• Represent Enterprise Data in platform reviews and technology governance, evaluating new capabilities for business value, architecture fit, and delivery risk, and coordinating with Principal Engineers on cross-domain standards, exceptions, and recommendations to standardize, consolidate, or retire platforms. 

People and delivery leadership 

• Lead, recruit, develop, and retain talent across the domain data engineering organization, including Staff Engineers, and build succession and capability plans for the domain. 

• Set clear goals, decision rights, priorities, performance expectations, and development plans; conduct performance reviews and support professional growth. 

• Manage assigned resources within established constraints, including contractor quality, delivery, and performance; forecast domain capacity and skill needs and provide renewal, staffing, and investment recommendations to the Engineering Leader. 

• Establish an operating model in which Staff and Principal Engineers engage stakeholders at the appropriate level and remain accountable for technical quality, design clarity, and delivery support. 

Stakeholder engagement 

• Own stakeholder alignment for the domain, partnering with business leaders to define outcomes and align technology decisions with enterprise objectives, with support and delegation as needed to Staff Engineers. 

• Maintain transparent relationships with business and technology leaders, communicating roadmap status, risks, dependencies, decisions, tradeoffs, and complex technical topics to engineering, business, and executive audiences. 

• Collaborate and negotiate with senior leaders on priorities, platform direction, operating constraints, and critical matters affecting the domain. 

Operational excellence and compliance 

• Drive adoption of enterprise data engineering and data quality standards and patterns within the domain, ensuring delivered solutions meet requirements for quality, reliability, observability, incident response, security, privacy, access, and lifecycle management. Define and monitor appropriate measures of domain delivery, quality, reliability, and stakeholder outcomes. 

• Ensure production support coverage and escalation paths are established for the domain, and serve as the point of escalation for significant incidents affecting domain systems. 

• Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork. 

• Support and comply with the company's Quality Management System policies and procedures, and partner with Security, Privacy, Compliance, and Business Continuity teams to meet applicable enterprise and regulatory requirements. 

• Regular and reliable attendance. 

• Ability to work on a mobile device, tablet, or computer screen and perform typing for approximately 90% of a typical working day. 

• Ability to travel up to 15% of working time away from the work location, including possible overnight or weekend travel. 

Minimum Qualifications 

• Bachelor's degree in Computer Science, Information Systems, Business, or a related field.

• 8+ years of progressively responsible experience in data engineering, data platforms, technology delivery, or related leadership roles. 

• 5+ years of direct people leadership experience, including managing engineering staff. 

• Demonstrated experience owning delivery, stakeholder outcomes, and operating performance for a data domain, platform, or program from planning through production support. 

• Demonstrated technical depth sufficient to direct and evaluate data engineering work and make priority, delivery, and technical-debt tradeoffs related to data architecture, integration patterns, data models, and platform decisions. 

• Demonstrated ability to lead delivery across direct reports, contractors, and dependent or matrixed teams, including risk, change, contractor, and dependency management. 

• Experience operating in a regulated or highly controlled data environment and delivering stakeholder outcomes at the required quality and on schedule. 

• Demonstrated ability to perform the Essential Duties of the position with or without accommodation. 

• Authorization to work in the United States without sponsorship. 

Preferred Qualifications 

• Experience with modern data platforms such as Databricks, event streaming architectures such as Kafka, and cloud data services in AWS, Azure, or Google Cloud Platform (GCP). 

• Experience delivering governed data products and semantic capabilities supporting analytics, machine learning, and AI use cases across commercial, financial, laboratory, clinical, or customer-facing business functions. 

• 5+ years in a regulated environment such as SOX, HIPAA, CLIA, Good Clinical Practice (ICH-GCP), FDA, ISO 13485, or IEC 62304. 

• Life sciences, diagnostics, or clinical laboratory experience. 

• Experience leading delivery across internal teams and contractor-based delivery models, and applying data privacy, security, access governance, lineage, retention, and business continuity practices.