Top Senior Data Management Jobs

Leads the data engineering roadmap and manages a team responsible for scalable ETL/ELT pipelines, cloud data platforms, data warehouses, integrations, governance, quality, and reliability. Partners with business, analytics, architecture, product, and AI/ML teams to deliver trusted data solutions, model-ready datasets, automation, and production AI/ML capabilities while establishing engineering best practices and mentoring technical staff.

Leads data analytics projects that generate insights for strategic decision-making. Develops visualization solutions with Power BI and Tableau, builds data pipelines, applies statistical modeling and predictive analytics, and manages data integrity and security. Collaborates with clients on tailored data solutions while coaching analytical teams, managing accounts, overseeing project success, and identifying business opportunities.

Leads compliance risk data analytics and testing strategy, plans and executes analytical projects, evaluates analytical tools, prototypes emerging practices, and translates technical findings for legal, compliance, risk, and executive stakeholders. The role also includes cross-functional partnership, written and verbal communication, and coaching and mentoring junior staff.

Leads the data engineering roadmap and manages a team of data engineers and technical leads. Directs scalable ETL/ELT pipelines, cloud data platforms, data warehouses, governance, quality controls, and reliability practices. Partners with business, analytics, architecture, and technology stakeholders to translate requirements into secure, dependable data solutions. Provides hands-on technical guidance while advancing platform capabilities, software development practices, and long-term data scalability.

Leads data analysis strategy for an analysis platform product, including data mining, modeling, testing, reporting, process improvement, and product analytics. Manages junior analysts, mentors team members, collaborates across business units, and supports large-scale databases and data storage systems. The role includes business intelligence, strategic experimentation, operational efficiency improvements, and consulting on production and data system design.

Leads data governance, risk mitigation, analytical tool validation, and program development for Global Payment Networks. Responsibilities include planning validation projects, assessing analytical methodologies and tool risks, researching industry practices, preparing reports and presentations, and coaching junior staff. The role requires managing concurrent projects and applying data analytics, risk management, statistical, and project management expertise to develop enterprise-wide controls and processes.

Lead a team delivering Power Platform and AI-driven analytics solutions (Power BI, Power Apps, Power Automate, Copilot Studio, Snowflake). Guide data modeling, governance, automation, and AI-powered workflows; prioritize initiatives, modernize reporting, and mentor engineers to drive scalable, self-service analytics and business application adoption.

Analyze large-scale data, build and validate models, improve processes and reporting, evaluate products and marketing initiatives, and consult on data systems. The role requires programming, strategic analysis, collaboration across concurrent projects, and leadership in a hybrid environment.

Leads and develops a Data Platform engineering team while owning delivery of complex data initiatives. The role establishes delivery discipline, assesses technical and implementation risks, partners cross-functionally, and drives production reliability, data quality, observability, incident management, and on-call readiness. It also guides the evolution of scalable data ingestion, transformation, lakehouse, cloud architecture, governance, and reusable platform capabilities.

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.

Leads enterprise analytical tool validation, including framework refinement, project execution, methodology risk assessment, technical research, and prototyping of industry practices. Communicates findings through reports and presentations, partners with cross-functional leaders to influence strategy, and coaches junior staff. The role also manages multiple concurrent projects and evaluates statistical and econometric models, data governance, and predictive analytics approaches.

Manage data analysis for transaction monitoring, risk identification, and compliance. Analyze high-volume transaction data using SQL, Python, Splunk, and visualization tools; conduct root-cause investigations; design risk data architectures; identify process and reporting improvements; advise business and product teams; and translate technical findings into executive recommendations. The role also involves stakeholder liaison, regulatory alignment, data integrity, and managing concurrent analytical projects.

Leads data analytics for commercial underwriting and portfolio management, using models, large datasets, BI, automation, and API integrations to manage credit risk, improve processes, and support strategic decisions. Develops analytical tools, reporting improvements, validation tests, and scalable data solutions while consulting on production and storage systems. Manages concurrent projects, collaborates across business units, and may lead people and project initiatives.

Lead a global analytics team to transform financial and operational data into actionable insights. Partner with stakeholders to align analytics with strategy, build scalable Power BI dashboards integrated with Snowflake, apply predictive modeling and ML, enforce data governance, drive automation with Python and Power Automate, and improve data architecture and reporting to inform decision-making and business performance.

Leads a data engineering team responsible for data modeling, batch and streaming ETL pipelines, analytics-ready datasets, data governance, and data quality. Hires, coaches, and manages engineers while setting technical direction and partnering with engineering, product, and business stakeholders. Oversees scalable data foundations across regulatory, customer, business, content, and growth domains, and advances practical AI automation and AI-ready infrastructure.

Leads client-focused data analytics initiatives within PwC’s Risk & Regulatory practice. Develops business intelligence, visualization, and advanced analytics solutions using Python, Oracle Business Intelligence, QlikView, and Spotfire. Builds stakeholder relationships, validates outcomes, drives process improvement, and applies systems thinking to solve complex business challenges. Oversees scalable deployments and coaches teams through ambiguous situations while delivering strategic insights and improved client performance.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

Leads data analytics strategy and project delivery for a global payments network. Mines and analyzes large-scale datasets, develops and validates models, improves processes and reporting, evaluates products and marketing initiatives, and supports new data systems. The role requires collaboration across business units, business intelligence expertise, strategic testing, and management of multiple concurrent projects. It may also involve people management and consulting on data storage and production systems.

The Senior Manager of Data Analysis will manage validation projects, assess analytical tool risks, and mentor junior staff while collaborating cross-functionally and enhancing analytical capabilities.

Lead the Managing Data Steward team for Small Business Bank to define and execute data management strategy, governance, quality controls, and data product development. Drive adoption of open-source and cloud-native (AWS) technologies, oversee data catalog health, monitor KRI's, manage data issue resolution, and report insights using advanced visualization. Coach and develop a high-performing analytics team while partnering with engineering and enterprise functions to standardize data flows and migrate on-prem systems to cloud.

Lead analytics engineering to design and maintain transformation layers, data models, and semantic layers. Ensure data quality, governance, observability, and single source of trusted metrics. Modernize reporting, support self-service analytics, collaborate across teams, review and test code, and leverage AI to improve analytics outputs.

The role involves leading a team to develop AI and ML solutions, manage customer interactions, and analyze large data sets using various technologies.

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Lead and coach teams to design, code, test, and deliver software solutions driving digital transformation for tax clients. Translate requirements into technical specs, perform code reviews, troubleshoot complex issues, maintain client relationships, and promote innovation and systems thinking to validate outcomes and improve products.