What are the responsibilities and job description for the Senior Director of Software Engineering position at JPMorgan Chase?
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As a Senior Director of Software Engineering at JPMorganChase within Employee Platforms in Enterprise Technology, you will lead the enterprise data platform strategy and execution across data engineering, data governance, artificial intelligence enablement, and agent-based workflow automation. You will own the end-to-end platform roadmap and help teams across the firm unlock trusted data products and responsible AI capabilities. You will build strong partnerships with stakeholders to ensure the platform is secure, compliant, cost-effective, and designed for long-term scale.
Job responsibilities
- Define and drive the enterprise data platform vision and roadmap aligned to business priorities and product strategy
- Lead data engineering delivery to build reliable, scalable pipelines and curated data products leveraging Databricks lakehouse capabilities
- Establish and evolve a data governance operating model across data quality, lineage, metadata management, stewardship, cataloging, and lifecycle management
- Implement and scale fine-grained, policy-based data access controls using Immuta to enable secure and compliant data sharing
- Build platform foundations for machine learning experimentation, deployment, and monitoring, and embed responsible AI practices into delivery
- Drive adoption of agent-based workflows that automate analytics, operations, and decision support through orchestration patterns and reusable capabilities
- Partner with Security, Legal, Privacy, and Risk to meet regulatory and control requirements, as applicable to the platform and its use cases
- Define and manage service level objectives, financial management practices, and cost/performance optimization for cloud data workloads
- Develop executive-level metrics and communicate platform health, value delivery, and risk posture to senior leadership
- Attract, develop, mentor, and retain high-performing leaders and teams across platform engineering, governance, and AI engineering
Required qualifications, capabilities and skills
- Formal training or certification on software engineering concepts and 10 years applied experience 5 years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise
- Demonstrated senior leadership experience building and operating enterprise-scale data platforms and data product ecosystems
- Deep expertise with modern lakehouse and cloud data platform architectures, including Databricks at scale
- Experience establishing and operating enterprise data governance capabilities, including data quality, lineage, metadata, and stewardship practices
- Hands-on experience implementing policy-driven data access controls and secure data sharing, including Immuta
- Experience enabling production machine learning capabilities, including model deployment, monitoring, and governance controls
- Proven ability to operationalize automated or agent-based workflow patterns in enterprise environments
- Strong knowledge of data architecture, distributed processing, data modeling, and platform reliability engineering
Executive-level communication skills with the ability to influence cross-functional roadmaps and senior stakeholders
Preferred qualifications, capabilities and skills
- Experience with Unity Catalog, Delta Lake, and modern operating models such as data mesh and data products
- Experience in regulated or highly governed environments with complex risk and control requirements
- Experience leading global, distributed engineering organizations
- Master’s degree in computer science, engineering, or a related field