Jobgether
Accountabilities:: Translate enterprise data engineering and platform strategy into an executable operating model, multi-year modernization roadmap, delivery priorities, governance standards, and measurable outcomes. Lead enterprise data engineering, platform engineering, data integration, and data operations, ensuring services are secure, scalable, resilient, observable, compliant, cost-effective, and operationally mature. Establish engineering standards, service-level objectives, recovery expectations, deployment practices, reliability standards, automation approaches, and continuous improvement processes. Direct multiple engineering managers and technical leaders while establishing organizational goals, performance expectations, accountability measures, workforce plans, succession strategies, and leadership development programs. Partner with Enterprise Architecture, Information Security, Compliance, Infrastructure, Data Governance, Analytics, Product, Finance, clinical, and business leaders to align technology execution with organizational priorities. Govern technology portfolios and investment priorities based on business value, operational risk, strategic alignment, cost, capacity, and expected outcomes. Develop business cases and execution plans for platform modernization, cloud transformation, automation, AI enablement, and emerging technology adoption. Own annual operating and capital budget planning for data engineering and platform services, including cloud spending, software licensing, procurement, vendor contracts, ROI analysis, and financial performance. Lead vendor strategy, negotiations, managed service relationships, licensing decisions, and vendor performance management. Monitor portfolio and organizational performance through executive dashboards, delivery health metrics, reliability indicators, cost trends, adoption measures, and business outcomes. Represent data engineering and platform capabilities in executive planning, governance, prioritization, and strategic investment discussions. Drive operational excellence through improved delivery predictability, production reliability, engineering quality, incident management, automation, release practices, and cross-functional alignment. Requirements: Bachelor’s degree in Computer Science, Information Systems, Engineering, or a 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 of experience leading managers and highly technical teams within 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. Proven ability to lead multiple engineering teams 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. Strong executive communication skills, including the ability to present technology strategy, investment tradeoffs, delivery risks, and business outcomes to senior leadership. Demonstrated success partnering across enterprise architecture, information security, compliance, analytics, product, finance, clinical, and business functions. Strong knowledge of modern cloud data platforms, data engineering practices, platform operations, automation, reliability engineering, data governance, cybersecurity, and operational excellence. Experience in healthcare or another highly regulated industry is preferred. Experience supporting AI, machine learning, advanced analytics, interoperability, enterprise reporting, and digital transformation initiatives is desirable. Experience with Databricks or comparable enterprise lakehouse, cloud data platform, data engineering, or analytics technologies is a plus. Strong understanding of cloud-native engineering, data protection, observability, automation, and enterprise data governance frameworks. Benefits: Base salary range of $158,804–$238,207. Full-time remote position in the United States. Opportunity to lead enterprise-wide data engineering and platform transformation. Executive-level exposure and collaboration across technology, business, clinical, analytics, security, and governance functions. Leadership responsibility across multiple engineering organizations and managers. Opportunity to influence AI enablement, cloud modernization, interoperability, enterprise reporting, and data-driven decision-making. Significant ownership of technology investment, platform economics, vendor strategy, and operational excellence. Professional growth through leadership development, organizational transformation, and enterprise-scale technology initiatives. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1