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The Engineering Manager, Data & AI Platform is responsible for leading teams that build, operate, and evolve Blackbaud’s enterprise Data & AI platform—the foundation that powers analytics, data products, machine learning, and agent‑based experiences across the company. This role blends people leadership, platform ownership, and technical strategy. You will manage engineers working across modern data and AI infrastructure (Lakehouse, pipelines, feature services, ML enablement, observability, and governance), while ensuring the platform is scalable, secure, cost‑efficient, and product‑oriented. Success in this role requires strong engineering judgment, the ability to operate in ambiguity, and a passion for building platforms that accelerate teams and unlock business outcomes for the nonprofit sector.
Job Responsibility:
Own and evolve core Data & AI platform capabilities, including ingestion, transformation, lakehouse architecture, feature services, and AI/ML enablement layers
Drive platform decisions aligned with Blackbaud’s Unified Data & AI Platform Strategy (modularity, interoperability, AI‑first design)
Partner with Architecture, Governance, and Security to ensure the platform meets trust, compliance, and Responsible AI standards
Balance build vs. buy decisions, prioritizing core competencies while reducing operational complexity
Lead teams to deliver high‑impact platform initiatives aligned to AOP priorities (legacy modernization, cloud migration, cost optimization, agent enablement)
Ensure platform reliability through operational excellence, including monitoring, incident management, and performance optimization
Establish clear roadmaps, milestones, and success metrics for platform initiatives
Hire, mentor, and grow high‑performing platform engineers across geographies
Provide regular feedback, coaching, and career development aligned with Blackbaud’s people strategy
Ensure every team member has clear goals, an active IDP, and opportunities to grow in modern Data & AI skills
Collaborate closely with Product, Data Science, Analytics, and Product Engineering teams to ensure the platform accelerates—not blocks—delivery
Influence standards and best practices across the Data Intelligence COE.
Requirements:
8+ years of experience in software, data, or platform engineering (.NET, Azure, Databricks, ADO preferred)
3+ years of experience managing and developing data engineering teams
Hands‑on experience with modern data platforms, cloud data lakes/lakehouses, distributed processing, streaming, APIs
Strong understanding of platform engineering principles and operating production systems at scale
Proven ability to lead through ambiguity and influence without authority.