Top Senior Data Management Jobs

Leads teams responsible for enterprise data engineering, analytics platforms, data modernization, governance, and AI context-layer development. Oversees data pipelines, models, integrations, metadata, ontologies, knowledge graphs, reliability, security, compliance, and cloud adoption. Sets strategy, manages budgets and resources, partners with executives and product leaders, drives risk controls and operational excellence, and develops engineering talent. The role also supports AI assistants and self-service analytics through governed enterprise data, semantic layers, and contextual metadata.

Leads software engineering teams responsible for modernizing enterprise data and analytics platforms. Oversees data pipelines, platforms, governance, reliability, cloud modernization, and reporting capabilities while building an AI context layer using semantic models, ontologies, knowledge graphs, and governed metadata. Manages strategy, budgets, delivery, risk, compliance, stakeholder partnerships, and talent development across complex initiatives.

Lead product analytics for Enterprise Data products, validating analytical tools, assessing methodology risks, researching emerging practices, and translating complex data into actionable insights. Manage validation projects, communicate findings through reports and presentations, and coach junior staff. The role requires advanced data analysis, statistical or econometric modeling, predictive analytics, large-dataset analysis, data governance, and people leadership.

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 data analysis strategy and manages junior analysts while mining large datasets, building and validating models, improving processes and reporting, evaluating products and marketing initiatives, and supporting data and storage system design. The role requires strong programming, business intelligence, data governance, and analytical leadership skills in a financial services environment.

Leads large-scale data engineering initiatives for Risk Tech, designing and delivering scalable cloud data platforms, pipelines, and applications. Responsibilities include architecture, data modeling, distributed processing, cloud warehousing, AI-enabled risk solutions, platform evaluation, operational resilience, and technical mentoring. The role collaborates with product managers, software engineers, analysts, and data scientists while independently driving architectural decisions and communicating technical outcomes to stakeholders.

As Senior Manager of Data Analysis, you will validate analytical tools, manage validation projects, assess quality and risks, and mentor junior staff.

Leads data engineering strategy, teams, and enterprise-scale platforms across Home Lending. Oversees cloud modernization, data lakes, streaming solutions, governance, quality, lineage, resiliency, and AI-ready data capabilities. Partners with technology, business, risk, architecture, and analytics leaders to deliver scalable solutions in a regulated financial-services environment. Responsibilities include organizational development, engineering standards, regulatory compliance, platform modernization, and operational excellence.

Leads enterprise data engineering strategy, teams, platform modernization, cloud adoption, AI-ready data capabilities, governance, resiliency, and regulatory compliance. Oversees data lakes, streaming solutions, data architecture, quality, lineage, metadata, and operational excellence while partnering with senior business, technology, analytics, risk, product, and architecture leaders.

Leads enterprise data engineering strategy, teams, platform modernization, cloud adoption, AI-ready data products, governance, and operational excellence. Oversees scalable data platforms, data lakes, streaming solutions, architecture, quality, lineage, security, compliance, and regulatory remediation while partnering with senior business, technology, analytics, risk, and product leaders.

Lead and grow a global data engineering team while establishing foundational data platforms and engineering standards. Design and oversee GCP-based pipelines, medallion data models, DataOps, monitoring, SLAs, CI/CD, governance, and data quality practices. Drive AI adoption across engineering workflows and build reliable, AI-ready data. Partner with business and technology stakeholders to prioritize roadmaps, deliver scalable solutions, and support data democratization.

Own the Marketing organization’s data and analytics strategy, including data structures, reporting requirements, governance, dashboards, and marketing funnel measurement. Partner with engineers, MarTech teams, vendors, and leadership to improve infrastructure, data quality, and operational efficiency. Lead executive-level performance analyses, operating-plan metrics, and C-suite reporting by translating complex cross-functional data into actionable strategic narratives.

Leads data analysis and AI-readiness initiatives for the personal loans business, including data governance, quality, automation, reporting, and analytics. Manages complex data analysis projects, improves processes and customer experiences, evaluates products and marketing initiatives, and collaborates across business units. Mentors junior analysts and contributes to data system design, business intelligence, and strategic testing.

Leads enterprise analytical-tool validation, including framework refinement, project execution, methodology risk assessment, technical research, prototyping, and validation reporting. Partners with cross-functional leaders to influence business strategy, solves complex analytical problems, and coaches junior staff. Requires substantial data analytics, open-source technology, statistical modeling, and people-management experience.

Leads people analytics initiatives that support talent strategy and workforce decisions. Responsibilities include developing analytics frameworks, managing data projects, building AI-powered data products and self-service tools, analyzing workforce data, prototyping automation solutions, and delivering insights to HR stakeholders and senior leaders. The role also involves data strategy, dashboard development, project execution, and potentially people management.

Leads data analytics and AI-readiness initiatives for the personal loans business. Responsibilities include improving data governance and quality, automating monitoring controls, building data abstraction layers, analyzing large databases, evaluating products and processes, enhancing business intelligence, and mentoring junior analysts. The role involves cross-functional collaboration, strategic testing, reporting improvements, and consulting on data systems while managing concurrent projects.

Leads enterprise healthcare data engineering strategy, cloud data platform modernization, warehouse and lakehouse architecture, ETL/ELT pipelines, streaming, interoperability, governance, data quality, and master data management. Manages data engineering, analytics, and platform teams while supporting AI/ML initiatives. Requires extensive healthcare data experience, leadership of large programs, cloud and data engineering expertise, knowledge of claims and clinical systems, and familiarity with HL7, FHIR, EHR platforms, and healthcare compliance.

Leads enterprise data risk measurement and analytics by defining metrics, building dashboards and data products, monitoring trends, translating policies into actionable insights, and presenting recommendations to executives. Manages junior analysts, drives cross-functional initiatives, supports data governance, applies AI to automate metrics, and performs analysis across large databases to improve processes, reporting, and business outcomes.

Manages data governance and pricing-related risks by overseeing processes, controls, reporting, documentation, and improvement initiatives. The role analyzes process data, identifies gaps, resolves policy-related issues, collaborates on enterprise projects, represents departmental interests, and trains junior staff and internal stakeholders. Responsibilities include maintaining procedures and diagrams, recommending process changes, supporting executive reporting, and ensuring adherence to data management and governance frameworks.

Own and operate Toast’s enterprise data governance program, including data domain ownership, governance council coordination, policy compliance, business glossary management, metadata standards, catalog adoption, maturity assessments, and data literacy training. The role partners with business stakeholders, data stewards, catalog teams, and leadership to improve data trust, compliance, discoverability, and quality. It requires governance, metadata, SQL, data catalog, program management, and workshop facilitation experience.

Leads a data analytics team developing AI automation strategies for card data. Responsibilities include validating analytical tools, assessing methodology quality and risk, researching emerging technologies, prototyping best practices, creating governance frameworks, communicating validation findings, and mentoring staff. The role requires expertise in data analysis, statistical and econometric modeling, large datasets, open-source data technologies, data governance, predictive analytics, and LLM-enabled strategies.

Leads the enterprise data platform strategy, architecture, governance, and evolution. Manages a central data team and enables federated self-service analytics across business functions. Builds AI-ready data pipelines, RAG and Graph RAG architectures, custom data applications, observability, cost optimization, and AIOps capabilities. Requires hands-on expertise with Snowflake, dbt, modern ETL, Python, SQL, CI/CD, and Data Mesh architectures, along with 5+ years leading technical data teams.

Leads enterprise data quality strategy for connected asset data, overseeing frameworks, KPIs, validation, monitoring, anomaly detection, governance, and automated quality controls across pipelines, APIs, and platforms. Manages data quality engineers and analysts while collaborating with engineering, analytics, product, architecture, telecom, and governance teams. Drives AI/ML-enabled quality improvements, supports releases and defect resolution, and communicates data quality risks to leadership.

Lead design and implementation of data infrastructure, pipelines, and warehouses using Azure Data Factory, Databricks, and Snowflake. Manage data modeling, quality, security, and analytics frameworks. Lead client accounts, mentor teams, and drive innovation to deliver data-driven business insights.

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.