Director, Data Engineering & Platform

Job Description Summary

‎ 

The Director, Data Engineering & Platform provides M4-level organizational leadership for the execution of the enterprise data engineering and platform vision and strategy established by the VP, Enterprise Data Platforms. The Director contributes to the evolution of the platform strategy in partnership with the VP, Director of Data Architecture, and peer leaders, but is primarily accountable for translating that strategy into an executable operating model, multi-year modernization roadmap, engineering governance, delivery priorities, and measurable enterprise outcomes.
This role owns the way enterprise data engineering and platform work is executed across the organization. The Director leads multiple engineering managers and cross-functional engineering organizations responsible for enterprise data engineering, platform engineering, data integration, data operations, and platform services. The role ensures that enterprise data capabilities are secure, scalable, resilient, cost-effective, and aligned to strategic growth initiatives, digital transformation, AI enablement, interoperability, enterprise reporting, and data-driven decision-making.
The Director balances organizational leadership, technology execution, financial stewardship, vendor strategy, operating discipline, and business partnership while developing a high-performing engineering organization capable of delivering enterprise-scale data products and platform services.

‎ 

How will you make an impact & Requirements

‎ 

Enterprise Strategy Execution & Platform Capability Leadership

• Own execution of the enterprise data engineering and platform strategy established by the VP, Enterprise Data Platforms, translating strategic direction into an operating model, multi-year execution roadmap, delivery priorities, and measurable outcomes.
• Contribute to enterprise platform vision, strategy, and technology direction in partnership with the VP, Director of Data Architecture, and peer technology leaders.
• Establish the enterprise data engineering operating model, engineering governance, standards, and operating principles adopted across the organization.
• Establish and maintain the platform evolution roadmap aligned with enterprise data strategy, modernization priorities, architectural direction, security requirements, and business objectives.
• Accountable for implementing enterprise data platform capabilities that support strategic growth initiatives, digital transformation, AI enablement, interoperability, enterprise reporting, and data product delivery.
• Evaluate emerging technologies, platform capabilities, and engineering practices to recommend pragmatic adoption approaches that improve enterprise outcomes.

Enterprise Platform Ownership & Modernization Execution

• Own enterprise data engineering operations and the way work is executed across platform engineering, data engineering, data integration, and data operations.
• Own execution of the enterprise platform strategy, including platform modernization, cloud transformation, lifecycle management, automation, and operational maturity.
• Own the modernization roadmap for enterprise data engineering and platform capabilities, ensuring roadmap execution remains aligned with VP strategy, enterprise architecture, and business priorities.
• Accountable for enterprise engineering service performance, technology resilience, organizational capability, and strategic platform evolution.
• Ensure enterprise platforms meet organizational expectations for availability, scalability, security, resiliency, regulatory compliance, observability, cost effectiveness, and operational supportability.
• Establish enterprise service-level objectives, operational performance standards, recovery expectations, and continuous improvement practices across platform and engineering services.

Engineering Organization Leadership & Span of Control

• Direct multiple engineering managers and cross-functional engineering teams responsible for enterprise data engineering, platform engineering, data integration, and platform operations.
• Direct Engineering Managers responsible for Platform Engineering, Data Engineering, Data Operations, and Data Integration.
• Develop workforce strategies including workforce planning, organizational design, staffing plans, succession planning, leadership development, recruiting strategy, and vendor strategy.
• Establish organizational goals, performance expectations, accountability measures, and execution disciplines aligned with enterprise priorities.
• Develop engineering and platform organizational leadership capability through succession planning, leadership coaching, management development, and clear accountability for delivery outcomes.
• Build an inclusive, collaborative engineering culture focused on innovation, continuous improvement, operational excellence, customer service, and reliable enterprise delivery.

Enterprise Architecture Partnership & Engineering Governance

• Define enterprise data engineering strategy in partnership with the Director of Data Architecture and the VP, Enterprise Data Platforms.
• Establish enterprise engineering standards, the platform evolution roadmap aligned with strategy, and operating principles governing data engineering across the organization.
• Partner with Enterprise Architecture, Information Security, Compliance, Infrastructure, Data Governance, Analytics, and Product leaders to maintain enterprise technology standards and practical delivery guardrails.
• Ensure engineering practices comply with organizational policies, regulatory requirements, cybersecurity standards, privacy expectations, audit requirements, and healthcare data protection obligations.
• Govern data engineering patterns, automation practices, reliability standards, deployment approaches, observability expectations, and operational controls across platform and engineering services.

Portfolio, Investment & Decision Influence

• Govern investment priorities across multiple portfolios and engineering organizations based on business value, operational risk, strategic alignment, cost profile, and organizational capacity.
• Contribute a strong Director-level voice with peers and the VP in portfolio prioritization, organization structure, capital investment, vendor selection, strategic technology direction, operating model design, and sourcing decisions.
• Develop business cases supporting modernization initiatives, enterprise data platform capabilities, automation investments, and emerging technology adoption.
• Partner with the VP and peer leaders to translate technology investment decisions into execution roadmaps, resource plans, delivery commitments, and outcome measures.
• Monitor portfolio performance using executive dashboards, key performance indicators, delivery health metrics, cost trends, and organizational outcome measures.

Financial & Vendor Management

• Own annual operating and capital budget planning and management for enterprise data engineering and platform services in partnership with the VP, Enterprise Data Platforms.
• Actively engage with the VP in annual planning, operating budget development, capital planning, technology investment portfolio management, ROI analysis, vendor management, and contract negotiations.
• Govern cloud spend, software licensing strategy, technology procurement, vendor contracts, managed service relationships, and vendor performance for enterprise data engineering and platform services.
• Lead investment prioritization, vendor negotiations, software licensing analysis, cloud spend governance, and business case development for platform and engineering capabilities.
• Ensure technology investments deliver measurable business value while maintaining financial stewardship, cost transparency, and accountability for platform economics.
• Present budget performance, investment recommendations, vendor considerations, and financial tradeoffs to the VP and executive stakeholders as appropriate.

Business Accountability & Executive Partnership

• Accountable for implementing enterprise data platform capabilities supporting strategic growth initiatives, digital transformation, AI enablement, interoperability, enterprise reporting, and data-driven decision-making.
• Translate business priorities into enterprise data engineering capabilities that improve operational performance, customer outcomes, clinical and business insight, and trusted data product delivery.
• Represent Data Engineering & Platform in executive planning, governance, prioritization, and strategic investment forums as delegated by or in partnership with the VP.
• Serve as a trusted technology execution partner to business leaders, analytics leaders, product leaders, clinical operations, finance, governance committees, and technology peers.
• Ensure enterprise data engineering capabilities support organizational growth, platform adoption, enterprise reporting, interoperability, AI enablement, and long-term technology modernization.

Operational Excellence

• Establish organizational metrics measuring platform adoption, engineering productivity, reliability, service quality, operational maturity, customer satisfaction, financial performance, and business value realization.
• Drive continuous improvement across engineering delivery, operational processes, automation, release management, platform performance, incident management, and organizational effectiveness.
• Ensure platform and engineering services are observable, supportable, cost transparent, well governed, and resilient enough to support enterprise-scale data products.
• Create durable management routines that improve delivery predictability, production reliability, engineering quality, and cross-functional alignment.

Leadership Responsibilities

• Direct multiple engineering managers and technical leaders across Platform Engineering, Data Engineering, Data Operations, and Data Integration.
• Establish execution roadmaps, organizational priorities, operating cadences, and accountability measures aligned with VP strategy and enterprise priorities.
• Build leadership capability through coaching, management development, succession planning, and talent development.
• Lead workforce planning, organizational design, recruiting strategy, vendor strategy, and capacity planning for the enterprise data engineering and platform organization.
• Foster collaboration across technology, business, clinical, analytics, governance, security, infrastructure, and operational organizations.
• Drive organizational accountability for delivery, quality, operational resilience, innovation, financial stewardship, and customer outcomes.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related discipline; Master’s degree preferred.
• 9–12 years of progressive experience in technology leadership, data engineering, platform engineering, enterprise data platforms, cloud data platforms, or related disciplines.
• 5+ years leading managers and highly technical resources in enterprise engineering, platform engineering, data engineering, integration, or data operations environments.
• Demonstrated experience leading enterprise transformation, platform modernization, cloud transformation, or large-scale data engineering initiatives.
• Experience directing multiple engineering teams and leading through managers, technical leaders, delivery partners, and vendors.
• Experience managing or materially influencing multi-million-dollar operating and capital budgets, technology investment portfolios, ROI analysis, vendor management, and contract negotiations.
• Executive communication experience, including the ability to present technology strategy, investment tradeoffs, delivery risks, and business outcomes to senior leadership.
• Demonstrated success partnering with enterprise architecture, information security, compliance, analytics, product, finance, clinical, and business leadership stakeholders.
• Strong working knowledge of modern cloud data platforms, data engineering practices, platform operations, automation, reliability engineering, data governance, cybersecurity, and operational excellence frameworks.

Preferred Qualifications

• Experience within healthcare or another highly regulated industry.
• Experience supporting enterprise AI, machine learning, advanced analytics, interoperability, enterprise reporting, and digital transformation initiatives.
• Experience governing enterprise cloud platforms, modern data architectures, data engineering operating models, and large-scale engineering organizations.
• Experience leading enterprise modernization and organizational transformation initiatives while balancing strategy, execution, cost, risk, and delivery capacity.
• Experience with Databricks or comparable enterprise lakehouse, cloud data platform, data engineering, or analytics platform capabilities.
• Strong knowledge of cloud-native engineering, enterprise data governance, cybersecurity, data protection, observability, automation, and operational excellence frameworks.

‎ 

Compensation Range:

$158,804.00

to

$238,207.00

The anticipated base salary range represents the Company's good-faith estimate of the compensation it reasonably expects to pay for this position at the time of posting. Actual compensation will be determined based on factors including experience, skills, qualifications, geographic location, internal equity, and business needs.