Top Senior Data Management Jobs

The role involves driving product strategy for data infrastructure, leading cross-functional teams, and implementing MLOps practices for data engineering solutions.

Acquire, clean, validate, store, and protect data from internal and external sources; develop and execute data architectures, ETL solutions, and lifecycle policies; prepare data for reporting and visualizations; lead projects through design, coding, review and deployment; perform root cause analysis and translate business needs into technical requirements.

Lead a quantitative modeling team to develop and govern credit underwriting, pricing, collections, and portfolio risk models. Collaborate with stakeholders on acquisition pricing, marketing optimization, M&A risk assessment, and model validation. Oversee model performance, governance, and implementation to support lending strategies and maximize profitability while minimizing credit losses.

Lead and grow a Data Engineering team to build a scalable analytics platform. Set technical direction for dbt and Snowflake, raise analytics engineering standards, enable domain experts to contribute high-quality models, introduce AI-assisted workflows, and partner cross-functionally to ensure reliable, understandable enterprise data.

Lead product analytics efforts to transform complex behavioral and usage data into actionable insights. Enable Amplitude platform adoption, build scalable dashboards and reports, ensure data quality and governance, partner with Product, Engineering, Sales, and Customer Success, and present findings to senior leadership to drive product and revenue outcomes.

Senior individual contributor leading regional execution of master data governance, quality, and stewardship. Drives data standards, remediation, integrations, MDM platform support, stakeholder alignment, compliance reporting, and large-scale data remediation across ERP/CRM/analytical systems.

Partner with Corporate Partnerships to centralize data, design dashboards and analytics tools, automate workflows, optimize CRM, and lead cross-functional projects to drive data-informed partnership decisions.

Lead renewals forecasting, predictive churn modeling, and impact measurement for CX. Build production-grade SQL models in Snowflake, integrate multi-source systems (Salesforce, Gainsight, Gong), apply LLMs/AI to automate workflows, drive data governance, and translate insights for executive decision-making to improve GRR and NRR.

Serve as the analytics bridge between marketing/operations and data teams: translate business questions and KPIs into clear product requirements, own delivery of treated tables, semantic layers, reports and dashboards, align stakeholders on a single source of truth, run gap analyses, document processes, and ensure delivered data products drive decision-making and adoption.

Lead and mentor data engineering teams to design, build, and govern enterprise data warehouses, lakes, and lakehouses. Architect scalable ETL/ELT and streaming pipelines, drive cloud migrations, enable BI/AI initiatives, and partner with Finance, Operations, and Supply Chain to deliver analytics and operational reporting.

Lead enterprise data strategy and governance, build AI-ready data infrastructure and BI systems, own SharePoint platform, partner cross-functionally to ensure data quality, access, compliance, and user adoption.

Lead data architecture and governance for Global Risk Management: define data products, remediate data quality and control gaps, design data solutions and platforms, lead cross-functional remediation efforts, and ensure completeness and accuracy of risk data for reporting and modeling.

Lead North America marketing analytics product portfolio, evolve MMM to causal and AI-native methods, prioritize roadmap and epics, oversee data engineers and scientists, drive adoption and value measurement for marketing effectiveness.

Lead second-line oversight of Data Quality controls: build and run a control monitoring program, manage annual oversight planning, perform design and operating effectiveness assessments, enforce sampling and evidence standards in the firm GRC tool, provide MI and challenge first-line owners, and lead a small team to drive remediation and reporting to senior management.

Lead marketing analytics by building dashboards, delivering consumer and market insights, evaluating campaign effectiveness, supporting planning/forecasting, and improving reporting and data governance to drive business growth.

Lead design and delivery of data infrastructure, including databases, warehouses, lakes, ETL, and data models. Define long-term platform strategy, ensure data quality and governance, partner with architecture and business stakeholders, evaluate emerging technologies, and simplify architectures to deliver reusable, cost-effective solutions while managing senior stakeholders and cross-functional teams.

Lead a scrum team of 5–7 data engineers to design, build, and operate Azure Databricks Lakehouse solutions. Set technical standards, drive data quality, oversee ETL/streaming pipelines, code reviews, CI/CD, and partner with architects and business stakeholders to deliver scalable, governed data products.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Lead and scale the data engineering function: design and maintain Azure-based data warehouse and high-performance ETL pipelines, ensure data quality and governance, mentor the team, collaborate with stakeholders, and drive data strategy and innovation.

Lead the global item master data strategy, centralize item repository, harmonize lifecycle processes, drive data quality and de-duplication, oversee large-scale migrations and platform enhancements, and manage a global team of data stewards and analysts to deliver cross-regional governance and operational consistency.

Lead a high-impact analytics team to build dashboards, reporting, and AI-powered customer analytics. Drive segmentation, personalization, experimentation, and ML operationalization by partnering with Data Science, Data Engineering, and business stakeholders while mentoring analysts and championing data literacy.

Manage day-to-day execution of regional assessment builds and readiness operations in Renaissance (Illuminate) DnA, maintain data quality and compliance, coordinate vendor data collection, develop documentation and training, support regional stakeholders, and continuously improve assessment and data workflows to ensure timely, accurate reporting.

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.

Lead a team to design, build, administer, and govern cloud-based enterprise data platforms. Partner with engineering, analytics, and infrastructure teams to deliver scalable, secure, reliable platforms (Snowflake/Databricks/Kafka/Airflow). Champion automation, IaC, CI/CD, cost optimization, and platform lifecycle management while mentoring staff and promoting best practices and continuous improvement.

Lead analytics for Paid Media strategy: design and deploy audience segmentation, ML models, and experimentation to optimize targeting, personalization, and digital acquisition. Apply emerging AI/GenAI techniques, collaborate cross-functionally to implement scalable data products, measure performance, and communicate insights to stakeholders.