Top Senior Data Management Jobs in Phoenix, AZ

Lead data engineering engagements to design, build, and maintain ETL/ELT pipelines and cloud data architectures. Manage client accounts and mentor teams, leverage tools like DataStage, AWS/Redshift, DB2/SQL Server, GoldenGate, and BI/visualization platforms to deliver analytics, performance tuning, and scalable reporting solutions.

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 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.

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 the enterprise data platform strategy and architecture, driving Snowflake/dbt-based platform evolution, self-service Data Mesh and medallion models. Build AI-ready pipelines, RAG systems, and observability/cost frameworks while managing a central data team, supporting federated BI, and executing hands-on technical work.

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.

Lead data engineering efforts within Technology Consulting: design data architecture and pipelines, implement AWS/Redshift and ETL solutions, support BI (QlikView/Oracle BI), coach teams, manage client relationships and SLAs, apply systems thinking to optimize outcomes and validate solutions with stakeholders.

Lead data governance activities including policy, retention, access, quality, and audits. Drive CEDS implementation, oversee external data requests and training, manage master data calendar, support budgeting, reporting and strategic planning, and maintain the Office of Data Governance website while coordinating with stakeholders and governance boards.

Support data-driven operations by sourcing, integrating, validating, and transforming data; build and maintain dashboards, agency scorecards, and reports; analyze KPIs to identify improvement and cross-sell opportunities; measure campaign effectiveness; ensure data quality; partner with stakeholders and technology teams; support monthly reviews and ad-hoc analytics requests.

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 CRA data analytics and reporting for regulatory compliance: manage a team, maintain CRA data platforms, ensure data quality and exam readiness, deliver Power BI dashboards and automation, support CRA exams, and drive modernization and governance across CRA reporting.

Lead strategic data evolution for Fund Administration clients, building dashboards, managing stakeholders, and translating business needs into actionable insights.

Acquire, clean, validate, store, and protect data from internal and external sources; develop and execute data architectures, ETL solutions, and lifecycle policies; prepare data for reporting and visualizations; lead projects through design, coding, review and deployment; perform root cause analysis and translate business needs into technical requirements.

The Senior Manager of Data Insights will lead a team to optimize data sharing and governance, develop data strategies, and deliver actionable business intelligence across Docker's operations.

Lead data engineering and architecture for data integration and data warehouse projects. Design and build data pipelines, define datasets and strategies, perform data modeling, configure and test ETL processes (Informatica), and work with GCP/BigQuery and Snowflake on Azure. Collaborate with stakeholders to prioritize business use cases and enable reporting.

Manage and develop a team of data analysts to deliver strategic analytics projects, ensure data accuracy, build reports and dashboards, translate insights into business recommendations, improve operational processes, coordinate cross-functional projects, and support budgeting and team development.

The Data Product Manager defines the reporting roadmap, manages KPI alignment, collaborates cross-functionally, ensures data quality, and leads continuous improvement in analytics processes.

Lead and scale the enterprise data hub: manage the data warehouse, build reliable ingestion and transformation pipelines, implement governance and data modeling best practices, deliver GTM-ready metrics, enable AI/ML use cases, prioritize the data roadmap, and lead/mentor a data engineering team.

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.

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 small data engineering team partnering with Engagement Marketing to build scalable ETL/ELT pipelines, ensure data quality, define marketing metrics, integrate trusted data with ad platforms, and drive the data roadmap to enable measurement and growth.