Manager Data Engineering AI

Accountabilities:: Lead and develop the data engineering team, providing strategic direction, technical guidance, coaching, mentoring, performance management, and professional development while building a high-performing and collaborative culture. Develop and implement data engineering architecture strategies that leverage AI and modern engineering practices while aligning technology decisions with business objectives and organizational priorities. Establish reusable templates, reference architectures, and engineering patterns for modern data pipelines connecting on-premises and cloud-based data sources. Partner with Architecture, Product, Business Leads, and Functional Product Managers to shape data product strategy and improve data literacy and understanding across organizational data assets. Monitor emerging AI trends, technologies, and engineering practices and identify opportunities to apply them to improve team efficiency, productivity, data architecture, and engineering capabilities. Lead and support strategic projects across data engineering and IT, applying appropriate project management methodologies and maintaining visibility into objectives, priorities, resources, and outcomes. Serve as a senior point of contact for internal stakeholders and clients when required, communicating technical concepts and strategic decisions clearly across business and technical audiences. Maintain significant ownership and influence over technology decisions within the assigned area, including optimizing service costs through effective use of internal teams, external resources, and development capabilities. Work closely with privacy and security stakeholders to ensure information systems and networks comply with internal standards, regulatory requirements, accreditation expectations, and applicable legal obligations. Support the development, implementation, testing, and continuous improvement of disaster recovery, emergency operations, backup, physical security, personnel security, access-control, and related plans designed to protect data integrity, confidentiality, and availability. Drive continuous improvement across engineering processes and practices while supporting internal and external customer satisfaction and ensuring that special projects and assigned objectives are completed effectively. Requirements: Bachelor’s degree or equivalent professional experience. 7+ years of combined experience in data engineering, IT, or project management, including at least 2 years of people-management experience. 2+ years of experience leading small to mid-sized projects using established project management methodologies, processes, and artifacts. 4+ years of experience working with complex datasets and modern data engineering technologies such as Hadoop, Spark, Databricks, AWS technologies, Snowflake, or comparable data integration and ETL platforms. 2+ years of experience working with AI engineering concepts and tools such as Retrieval-Augmented Generation (RAG), prompt engineering, LangChain, LangGraph, or similar technologies. Familiarity with MLOps and LLMOps capabilities and platforms, including tools such as DataRobot or comparable solutions. At least 2 years of hands-on experience in software development and database management, with the ability to understand and guide technical implementation decisions. Proficiency with Microsoft Office Suite and strong ability to communicate technical and complex information clearly to diverse audiences. Experience with healthcare data, particularly within a data operations environment, is preferred. Experience working in Agile environments is preferred. Strong leadership, coaching, mentoring, conflict-resolution, and stakeholder-management capabilities, with the ability to build trust and maintain effective relationships through challenging or ambiguous situations. Ability to translate complex technical information into clear, accessible messages, establish strategic priorities, manage competing demands, allocate resources effectively, and make sound decisions even when precedent or complete information is unavailable. Ability to adapt quickly to changing priorities, processes, technologies, and team dynamics while proactively identifying opportunities for individual, team, and process development. Ability to work effectively in a remote environment with a dedicated, secure workspace and reliable high-speed internet connectivity. Benefits: Fully remote position within the United States, with interviews conducted virtually. Base compensation range of $145,000–$175,000 USD , with specific offers determined by factors including experience, education, skills, certifications, and business needs. Eligibility for discretionary bonus consideration. Medical, dental, and vision insurance options. Disability and life insurance coverage. 401(k) savings plan. Paid family leave. 9 paid holidays per year. 17–27 days of paid time off (PTO) per year, depending on level and length of service. Opportunity to lead AI-focused data engineering initiatives and work with modern technologies spanning cloud data platforms, AI engineering, data architecture, and MLOps/LLMOps. Significant technical and organizational leadership scope, including team development, architecture strategy, data product direction, and cross-functional technology initiatives.