Top Senior Data Management Jobs

Lead a team to design, build, and maintain scalable cloud and big-data systems. Oversee streaming and batch pipelines, data architectures, ingestion, transformation (Spark), modeling, deployment pipelines, and stakeholder collaboration to deliver robust data products and analytics-ready platforms.

Lead design and delivery of data infrastructure, pipelines, and scalable architectures (Snowflake, Azure Data Factory). Oversee data quality, security, and deployment, collaborate cross-functionally, and coach teams to solve complex data challenges and validate client outcomes.

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.

The Manager of Data Architecture leads the design and governance of the Ad Sales data ecosystem, managing a team to ensure scalable and trusted revenue data systems. Responsibilities include data architecture, system oversight, governance, and business partnership with Sales and Finance.

As a Senior Manager, Data Analysis, you will validate analytical tools, enhance technical skills, manage projects, and coach junior staff while collaborating cross-functionally.

Lead a team delivering enterprise-wide model risk reporting and AI-driven automation. Build and deploy scalable ML/AI solutions, conversational reporting, multi-agent workflows, and centralized data integrations. Drive analytics strategy, validate models and data, improve reporting and operational efficiency, and collaborate across business units.

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.

Manage the Data Lake engineering team at Apex Fintech Solutions, driving technical initiatives, collaborating with stakeholders, and ensuring scalable data solutions. Responsibilities include team leadership, Agile facilitation, technical strategy, risk management, and establishing best practices in data engineering.

Lead and grow a data engineering team, define data platform architecture and reliability (warehouse, ingestion, transformations, orchestration), set engineering standards, partner cross-functionally to support analytics and ML, and translate technical decisions for executive stakeholders.

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

The Senior Manager of Data Engineering leads developers in creating technical solutions using various technologies, mentoring staff, and collaborating to enhance cloud-based services for financial empowerment.

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.

The Senior Manager will lead cross-functional analytics projects, validate analytical tools, and mentor junior staff while driving data-based business strategies.

As a Senior Manager, you will lead cross-functional data analytics projects, validate tools, and influence business strategies while mentoring junior staff.

Lead and grow the data platform engineering team; own technical direction for pipelines, infrastructure, orchestration, and standards; drive reliability, observability, cost optimization, and governance; recruit and mentor engineers; collaborate cross-functionally to align platform priorities with business needs and enable analytics and ML workloads.

The Data Strategy Manager will lead projects to deliver data strategy solutions in Life Sciences, manage client relationships, and mentor team members.

Manage the data architecture and strategic planning for the Sales team, optimizing processes through data and AI for targeting accounts and pricing strategies.

Provide Regional Content Management and GEOINT support. Advise on data delivery methods, analyze data for enhancements, and develop workflows. Present instruction on GEOINT usage and maintain map services using ESRI Portal technology.

Build and lead the Compliance data function, owning data products for Customer Risk, Transaction Monitoring, AML, Sanctions. Design and implement data risk frameworks (quality, usage, lineage), enforce data contracts between producers and consumers, maintain end-to-end lineage with Engineering, and drive a risk-based data roadmap aligned with compliance requirements.

The Manager, Data Analysis will lead a team of analysts, leveraging analytical skills and models to drive data strategy and improve customer experiences. Responsibilities include mining complex data, enhancing operational efficiencies, and mentoring junior team members while collaborating across business units.

Serve as strategic operator for Data & Analytics: run planning and quarterly business review processes, lead cross-functional strategic programs, identify AI and analytics opportunities, produce executive narratives and decision frameworks, and scale operating mechanisms to connect DNA strategy to company OKRs and delivery.

Lead a team building and operating scalable data pipelines and platform infrastructure. Hands-on coding, code review, and delivery ownership; enforce best practices for testing, CI/CD, observability, and cost optimization. Mentor engineers, recruit talent, and collaborate with analytics, data science, and business stakeholders to translate requirements into platform solutions.

The role involves leading a team of data analysts, driving strategy through analytics, and improving data processes and reporting. Candidates should have experience with data analysis and programming, mentoring, and business intelligence.

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 and grow a data engineering team that designs, builds, tests, and operates large-scale data pipelines and warehouses. Partner cross-functionally to translate requirements, ensure data quality, observability, SLAs, security, and governance, and drive automation and performance for analytics, ML, and product use cases.