Top Data Management Jobs in Salt Lake City, UT

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 design and implementation of data infrastructure, pipelines, and integrations using cloud platforms. Manage teams and client accounts, ensure data quality, security, and compliance, deploy scalable solutions (Databricks, Snowflake), mentor junior staff, and identify data-driven business opportunities.

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.

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.

Build and lead the Compliance data function, owning data products for Customer Risk, Transaction Monitoring, AML, Sanctions. Design and implement data risk frameworks (quality, usage, lineage), enforce data contracts between producers and consumers, maintain end-to-end lineage with Engineering, and drive a risk-based data roadmap aligned with compliance requirements.

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.

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

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

The role involves managing Data Success Managers, overseeing data operations, supporting partners, and improving team workflows to deliver quality service.

Lead a team of data and infrastructure engineers to develop cloud-based data systems and solutions for analytics, ensuring best practices in data management and MLOps.

Oversee design, build, and maintenance of data pipelines and architectures, ensuring data reliability and supporting analytics and reporting needs.

The Senior Manager will oversee operations across technology functions, lead strategic initiatives in Data & AI, and ensure effective management of technology projects and resources. Responsibilities include engaging stakeholders, identifying risks, and fostering continuous improvement within the team.

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

Own the conversion of raw alternative datasets into scalable, AI-ready data products. Define methodologies, metric definitions, and guardrails for AI-driven insights. Partner with engineering, product, and customers to expand use cases, ensure data quality, validate changes, and manage incidents to deliver reliable, explainable data products at scale.

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

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.

The Data Success Manager will source, collect, and manage data for partners, ensure data quality, and support campaign activity, requiring SQL and Python skills.

The Manager, Data Success Management oversees Data Success Managers, manages data operations, supports partners, improves workflows, and ensures data quality.

Lead a global, hands-on data engineering team building large-scale Databricks/PySpark pipelines, production datasets, customer-facing data feeds, AI-ready analytical datasets, and data quality/observability systems. Partner cross-functionally, use AI coding tools to accelerate delivery, and ensure operational excellence, reliability, and documentation for investor-facing products.

Administer and maintain CRM and data systems (EveryAction, Salesforce, BigQuery, CARTO), respond to staff and affiliate data/tech requests, ensure data quality and de-duplication, create and deliver training materials, build network capacity, manage vendor/consultant relationships, and travel occasionally for in-person trainings and support.