Top Senior Data Management Jobs

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.

Manage a team of 2–3 analysts while remaining hands-on with SQL, dbt models, dashboards, and complex operational analyses. Lead ambiguous, cross-functional initiatives, deliver recommendations to senior stakeholders, ensure data quality, and improve reporting automation. Partner on AI analytics strategy, data readiness, agent evaluation, and human-in-the-loop governance. Responsibilities include coaching, prioritization, performance management, technical review, KPI development, and operational insights across customer experience, fraud, payments, workforce management, and VIP functions.

Leads a small team responsible for enterprise data engineering, data warehousing, database administration, integrations, SharePoint, Nintex automation, Power BI enablement, governance, security, and operational reliability. The role owns Microsoft Fabric and EDW architecture, builds and supports ETL/ELT pipelines, manages platform roadmaps and vendors, applies AI-enabled automation, and partners with IT and business stakeholders to deliver trusted, secure, governed data services.

Build and lead Crown Castle’s Data and AI Governance Engineering capability. Establish governance, data quality, metadata, lineage, access, observability, and AI governance strategies while automating controls and workflows across Databricks and the broader data ecosystem. Remain hands-on with prototyping, testing, troubleshooting, and reusable engineering patterns. Partner with technical, legal, security, risk, audit, architecture, and business teams to improve data trust, accountability, discoverability, and responsible AI adoption.

Leads data engineering, business intelligence, and analytics teams; oversees data pipelines, integration infrastructure, database architecture, CI/CD practices, and enterprise data platform strategy. Partners with business and technology stakeholders to define requirements, improve data capabilities, maintain Ubuntu-based services, and deliver reporting and KPIs to leadership. Responsible for team hiring, development, mentoring, operational health, and technical execution across analytics and data integration platforms.

Manages and advances an enterprise data governance program, including governance standards, stewardship, metadata, definitions, lineage, semantic models, data quality, and reporting consistency. Leads governance committees, resolves cross-functional data issues, supports data literacy, and embeds governance into analytics, reporting, systems, and business processes. Partners with technical and business stakeholders, supervises staff, and drives accountability across the organization.

Generate actionable insights from large and diverse datasets using statistical and machine learning methods. Develop predictive models, segmentation approaches, data pipelines, and features to support health programme targeting and evaluation. Design and analyze behavioural experiments, translate technical findings into clear narratives, and collaborate with internal teams and external partners to inform policy and programme decisions.

Leads hands-on enterprise data engineering and architecture across Microsoft Fabric and Azure. Designs and optimizes data warehouses, pipelines, integrations, data models, BI solutions, DevOps practices, security, reliability, observability, and data quality standards. Troubleshoots complex production issues, guides AI enablement and Power BI capabilities, conducts technical reviews, and mentors engineers. The role requires advanced SQL, T-SQL, Python, PySpark, Data Vault, dimensional modeling, cloud data platform expertise, and technical leadership.

Leads marketing data analysis, audience segmentation, campaign targeting, and performance insights using SAS, SQL, Python, Databricks, and Salesforce Data Cloud. Translates marketing strategies into campaign specifications, develops and activates customer audiences, validates targeting logic, and communicates recommendations to marketing, business, compliance, and technology stakeholders. The role improves targeting methodologies, supports campaign execution, identifies growth opportunities, and provides specialized business insights while ensuring governance and regulatory alignment.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

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.

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 enterprise data and analytics strategy, governance, technology roadmaps, and scalable data solutions. Oversees data engineering, business intelligence, reporting, analytics, data quality, integration, and warehouse or lakehouse environments. Partners with business and technology leaders to deliver data products, dashboards, automation, and AI-enabled solutions. Manages resources and vendors, prioritizes initiatives, ensures security and compliance, and develops analytics talent while driving data-informed decision-making.

Leads a high-performing team managing Google Cloud analytics marts and enterprise data assets. Oversees data quality, testing, UAT, governance, documentation, incident resolution, and data literacy initiatives. Analyzes datasets, translates business needs into technical requirements, consults on data usage, and partners with analytics, operations, and technology teams to improve data capabilities and align solutions with enterprise strategy and technology roadmaps.

Leads philanthropy data strategy, reporting, CRM administration, and technology operations. Oversees data governance, system integrity, dashboards, forecasting, campaign reporting, integrations, vendor relationships, automation, and continuous improvement. Partners with philanthropy leadership to improve fundraising performance and operational efficiency, while ensuring data quality, security, compliance, and documentation. Supervises and develops staff and serves as the subject matter expert for philanthropy data and technology.

Owns data integrity, quality assurance, remediation, standards, and governance for Development data. Leads audits, maintains data definitions and business rules, assigns corrective actions, facilitates governance decisions, and partners with analytics, CRM, fundraising, finance, IT, compliance, and legal teams. Develops training, monitors stewardship accountability, resolves data-quality issues, and ensures reliable reporting and downstream business processes.

Leads the Health Fund’s Data Engineering Team and oversees enterprise data warehouses, pipelines, integrations, governance, testing, and data quality initiatives. Provides technical leadership, manages staff, translates business requirements into scalable solutions, and partners with business, technology, QA, infrastructure, and external vendors. Ensures data platforms meet performance, reliability, privacy, security, regulatory, and operational requirements while developing data strategy, architecture, documentation, standards, and best practices.

Manages global trade data and automation initiatives by building dashboards, reporting tools, and SharePoint environments. Collects, cleans, validates, and analyzes large datasets to identify trends, anomalies, and improvement opportunities. Collaborates with program management, audit, investigations, disclosure, and technology teams to deliver actionable insights, monitor data health, and support compliance-related reporting.

Leads the customer master data governance program and serves as business owner for the Informatica MDM platform. Oversees governance policies, data quality, customer hierarchies, stewardship operations, source onboarding, platform enhancements, and AI-enabled matching and deduplication. Partners with business, IT, technical teams, and external providers to define requirements, manage priorities, resolve issues, and improve data processes. Performs hands-on testing, validation, reconciliation, and user acceptance activities before platform changes are deployed.

Manages corporate real estate spatial data, CAD drawings, CAFM systems, space allocation models, reporting, data governance, and system administration. Supports project management, occupancy planning, and move management by maintaining accurate as-built drawings, monitoring space data, establishing global standards, coordinating system integrations, training users, and recommending process improvements. Requires expertise in CAD/CAFM, drafting, space planning, and corporate real estate data management.

Leads a team of data analysts supporting Marketing, Digital, Customer, and DEI functions. Oversees dashboards, reporting, advanced analytics integration, data requirements, quality assessment, visualization, and business insights. Partners with Data Science, Data Engineering, Technology, business units, and vendors to translate requirements into actionable solutions and drive analytics adoption. Coaches analysts, manages priorities, and supports strategic use cases using SQL, Python, cloud data platforms, experimentation, and business intelligence tools.

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 engineering teams responsible for designing, developing, and maintaining scalable data systems, integrations, pipelines, warehouses, and governance solutions. Provides technical leadership, mentorship, architecture guidance, and cross-functional coordination to meet business requirements, service-level agreements, compliance standards, and operational goals. Evaluates emerging technologies and oversees internal and outsourced resources supporting master data management, analytics, data warehousing, and enterprise information systems.