Top Tech Jobs & Startup Jobs in Los Angeles, CA

Leads strategic planning, portfolio governance, organizational performance management, resource planning, roadmap integration, and execution coordination for a global Decision Intelligence and Analytics organization. The role aligns investments, priorities, resources, and transformation initiatives; manages leadership operating rhythms, performance reporting, dependencies, and cross-functional governance; and supports senior leaders across matrixed organizations.

Leads enterprise analytics modernization and productivity strategy, governance, roadmaps, prioritization, workflow reengineering, and operating model transformation. Partners with AI and platform teams and business stakeholders to define requirements, enable AI-supported ways of working, establish reusable standards, drive adoption, and measure value. The role owns modernization backlogs, capability roadmaps, governance frameworks, and change initiatives while coordinating globally integrated teams.

Leads analytics governance and stewardship operations, portfolio administration, organizational reporting, knowledge management, and operational modernization. Administers governance forums, issue intake, escalation tracking, dashboards, scorecards, planning processes, reusable tools, workflows, and self-service resources. Coordinates cross-functional execution across US and HYD teams, supporting capability leaders without owning strategy, technical architecture, engineering, or governance decisions.

Owns a portfolio of NovaOS capabilities from concept through delivery, adoption, and continuous improvement. Manages backlogs, roadmaps, prioritization, requirements, user stories, release planning, and product metrics. Partners with stakeholders, Engineering, AI, UX, Data Science, and Architecture teams to deliver enterprise AI-enabled products aligned with governance, Responsible AI, and business objectives.

Leads implementation and adoption strategy for enterprise transformation initiatives, partnering with business and technology teams from solution design through deployment and stabilization. Assesses stakeholder impacts, readiness, behavioral changes, risks, and adoption metrics; develops deployment, training, communications, and sustainment plans; equips leaders and sponsors; removes barriers; and captures reusable practices. The role requires influencing executives and frontline teams across business, technology, learning, communications, and operational functions.

Lead enterprise data engineering standards, governed pipelines, data contracts, observability, quality controls, lineage, testing, and compliant data delivery. Partner with governance, privacy, architecture, modeling, and platform teams to ensure reliable, traceable, protected data products. Monitor operational performance, automate deployment and validation, and resolve pipeline and data reliability issues across complex enterprise environments.

Lead enterprise data governance capabilities across KPI governance, governance platforms, or data access and security. Responsibilities include defining frameworks and controls, managing governance platforms and access policies, partnering with business, technology, privacy, legal, and compliance teams, overseeing vendors, and reporting governance maturity and operational health. The role supports data strategy, trusted data access, Data Command Center capabilities, and responsible data use in a regulated environment.

Leads the strategy, architecture, development, deployment, and optimization of an agentic AI platform. The role transforms products and workflows into scalable AI experiences, oversees AI engineering operations, establishes security and governance practices, evaluates models and orchestration frameworks, and drives observability and continuous improvement. The Associate Director partners with product, data, architecture, security, and business teams while building and mentoring high-performing engineering teams.

Leads the design and implementation of AI-powered data pipelines, enterprise feature stores, analytics-ready repositories, and self-service data access layers. Builds automated feature engineering, data quality, observability, and governance capabilities for large-scale data science workloads. Partners with Enterprise IT, establishes data availability and quality SLAs, integrates structured and unstructured data sources, and leads teams delivering scalable analytics infrastructure.

Lead enterprise metadata strategy, standards, governance, capture, curation, validation, lineage, and lifecycle management across data products and business assets. Partner with data governance, engineering, quality, analytics, modeling, and stewardship teams to improve data trust, discoverability, reuse, and AI readiness. Drive metadata automation, catalog synchronization, certification support, issue remediation, and stakeholder communications across a complex enterprise data environment.