Top Senior Data Management Jobs

Lead end-to-end delivery of governed CRM data products for CIB Sales: define requirements, ensure data quality, SLAs, documentation, and deliver reusable datasets, APIs, dashboards and ML-ready assets while partnering with stakeholders and platform teams.

Lead portfolio-level product operations and change management to drive adoption of AI and analytics tools. Design and run persona-based training, measure adoption and effectiveness, coordinate cross-product priorities, and enable operational efficiency by partnering with HR, analytics teams, and stakeholders to ensure successful AI upskilling and sustained value realization.

Lead and develop a team delivering data conversion for customer implementations. Drive adoption of AI and automation, manage complex/at-risk migrations, track KPIs, and improve processes through experimentation and transformation.

Lead data analytics for the Hotels Travel Agency team: define KPIs, build dashboards, run A/B tests, conduct deep-dive analyses, troubleshoot tracking and data quality, and partner with product and engineering to improve data models and accessibility.

Lead validation of enterprise analytical tools: refine frameworks, plan and execute validation projects, assess methodology quality and risk, prototype best practices, communicate findings, and coach junior staff while influencing business strategy.

The Manager of Data Analysis leads a team to leverage analytics for improving customer experience, driving strategy, and implementing data models. Responsibilities include data mining, process improvement, and project lifecycle management, all within a collaborative environment.

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.

Lead design and rollout of a fit-for-purpose data governance program: manage data lifecycle, implement governance frameworks and tools, drive data catalogs/lineage, upskill stewards, define KPIs, and partner cross-functionally to improve data quality, compliance, and usability.

The role involves driving strategy through data analytics, leading a team, implementing process improvements, and developing data models. Requires strong analytical, problem-solving, and leadership skills.

Lead a team to operate and scale CarGurus' data platform across ingestion, orchestration, storage, and observability. Own roadmap, SLAs, cost, security, and quality controls; improve developer experience; collaborate with product and stakeholders to prioritize initiatives, resolve incidents, and drive platform reliability and scalability.

Lead design and implementation of scalable data infrastructure, pipelines, and transformations using cloud platforms. Build and optimize data warehouses (Snowflake, Databricks), orchestrate workflows (Airflow, Hadoop), ensure data quality and security, and coach teams to deliver analytics solutions that drive tax practice insights and client outcomes.

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 grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.

Lead design and execution of an enterprise data controls and governance program. Assess controls, define standards, implement data quality checks and monitoring, support platform migrations, and enable AI-ready data. Partner with cross-functional teams, manage a team of analysts, and ensure regulatory compliance for critical ratings and enterprise datasets.

Own and build merchant and advertiser data marts powering retail media and reporting. Design standards, implement Hive→Iceberg migrations, develop dbt models and Airflow DAGs, build cataloging and PII/audit tooling, enforce Trino+CloudSentry access policies, operate production marts with on-call duties, and coordinate cross-functionally with Sales, BizOps, and Analytics.

Lead development and execution of an enterprise analytical tools validation framework. Plan and run validation projects, assess methodology quality and tool risk, prototype best practices, communicate results via reports/presentations, partner cross-functionally, and coach/mentor junior staff while driving technical and analytical solutions.

Lead enterprise validation of analytical tools for the card business: design and execute validation projects, assess tool methodologies and risks, prototype best practices, communicate results, manage multiple projects, and mentor junior staff.

Lead and grow a data engineering team to build and maintain data models, batch and streaming ETL pipelines, and governance practices. Partner with platform, product, and business stakeholders to ensure reliable, governed, and scalable data for BI, ML, and operations while driving AI strategy and technical direction.

The Senior Manager, Data Analysis will validate business impacting analytical tools, assess methodologies, coach junior staff, and execute validation projects.

Lead and grow a data engineering team to build scalable, cloud-native multi-cloud Lakehouse data products using Databricks, Spark, Delta Lake and near real-time streaming. Drive migration from legacy systems, enable AI/ML and GenAI use cases, ensure observability, data governance, CI/CD, and collaborate with product, analytics, security and architecture teams to deliver customer and marketing data solutions.

Lead a team evaluating new and existing data assets, standardize due-diligence and analytical methodologies, validate data quality and business value, partner with Product and Technology to support onboarding and OneTru cataloging, establish governance and lineage standards, and coach team members to drive data-driven product and revenue decisions.

The Senior Manager will lead cross-functional data analysis projects, manage teams, validate tools, and mentor junior staff while enhancing technical skills.

Lead the migration domain to ensure accurate, complete, repeatable migration of customer, account, product, and transactional data. Oversee migration automation/tooling and legacy data hygiene. Own analytical frameworks, data mapping, and reconciliation controls to ensure institutional and regulatory confidence. Lead cross-functional teams and drive product outcomes aligned with business and technology objectives.

Lead design and delivery of reusable, AI-ready data products and interoperable data-engineering artifacts for retail-banking portfolios. Manage data product lifecycles, ensure data integrity and governance, create self-service analytics, and align technology and business teams in a matrixed organization.

Lead and grow a data platform engineering team to build and maintain a petabyte-scale data lake and infrastructure. Drive platform roadmap, scale systems globally, collaborate cross-functionally, and embed best practices for security, privacy, and AI transformation.