Top Data Management Jobs in Los Angeles, CA

Lead data-driven strategies and analytics at PwC, motivating teams to improve business performance and decision-making through advanced techniques and collaboration.

As a Manager in Data Governance at PwC, you will lead data governance strategies, supervise teams, manage client accounts, analyze data for decision-making, and ensure compliance with standards.

As a Senior Manager in Data Engineering, you will lead teams to design data architectures, develop data solutions, manage client engagements, and ensure compliance with data governance policies.

As a Senior Manager in Data and Analytics Engineering at PwC, you'll design data architecture strategies for healthcare, mentor teams, influence stakeholders, and enhance healthcare operations through data solutions.

Lead data engineering projects, develop and implement data pipelines and architecture strategies, manage data quality, and mentor team members at PwC.

The Senior Manager of Data Engineering will build a data platform, lead a team, and ensure data accessibility to support AI and business operations.

Lead and scale enterprise data governance operations: manage the data domain model and business glossary, run governance council operations, enforce data policies and compliance (SOC 2, GDPR/CCPA), drive catalog adoption and data literacy, and measure governance maturity and ROI through dashboards and remediation workflows.

Oversee data ingestion and transformation, manage finance data sources, ensure scalability and reliability of data platforms, and collaborate with stakeholders to align data engineering with organizational goals.

This role involves applying advanced data science and machine learning methods to healthcare data, leading teams, managing client relations, and developing analytics products for payers, while mentoring junior staff.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Manage Finance-focused data products, collaborating with teams to define requirements and drive delivery for financial analysis and reporting.

Lead strategy and delivery of enterprise streaming and social data products that serve as authoritative sources of truth. Ensure AI-ready, governed, semantically consistent data with metadata, lineage, observability, SLAs, and adoption plans. Partner with analytics, engineering, and commercial teams to define metrics, manage external data sources, enforce data contracts, and drive AI and predictive use cases for music consumption and audience insights.

Lead data taxonomy, governance, metadata, and documentation for data products. Own definitions, lineage, delivery operations, client-facing issue management, and cross-functional governance to ensure reliable, consistent, and discoverable data assets.

Lead data-focused consulting projects end-to-end: manage stakeholders and teams, translate business problems into data solutions, perform hands-on SQL (and occasional Python) development, design data models and warehouses, build BI visualizations, run workshops, mitigate risks, and contribute to practice growth and mentorship.

Lead architecture and delivery of Radiant's enterprise data platform and AI strategy. Own vendor evaluations for secure AI tooling, mentor engineers, coordinate with software teams, ensure Databricks-based integrations and dashboards meet ITAR/EAR compliance, and act as a hands-on technical leader.

The Master Data Manager leads master data strategy and governance, ensuring data quality and compliance across the organization, while managing a team and engaging stakeholders.

The Senior Manager of Data Engineering will lead a team, manage data platforms, drive modernization, oversee budgets, and ensure data solutions are scalable and reliable.

Lead a team owning master data governance for customers, products, and suppliers across SAP S/4HANA and integrated systems. Establish data standards, policies, and workflows; drive cross-functional initiatives, oversee ticketing and SLAs, perform root-cause analysis, and support PLM/IBP integrations while coaching and developing staff.

The Manager, Data Analytics leads initiatives transforming data into actionable insights for business growth, mentoring analysts and optimizing ecommerce performance through advanced analytics and strategic partnerships.

The Manager, Data Management leads a firm-wide data management program, ensuring data quality and accountability across master data domains while partnering with stakeholders and managing staff.

Lead Data Governance and Data Enablement teams within Investment Operations to design scalable governance frameworks, improve data quality, enable self-service, and drive AI-enabled solutions. Partner with business and technology stakeholders, develop talent, and translate data strategy into actionable roadmaps that improve enterprise data management and insights.

The role involves leading the data governance team, managing IT projects, collaborating with stakeholders, and ensuring continuous improvement of processes. Responsibilities include strategic planning, client management, and optimizing resource utilization, while overseeing governance activities and departmental management.

Serve as the analytics bridge between marketing/operations and data teams: translate business questions and KPIs into clear product requirements, own delivery of treated tables, semantic layers, reports and dashboards, align stakeholders on a single source of truth, run gap analyses, document processes, and ensure delivered data products drive decision-making and adoption.