Top Senior Level Data Management Jobs

Tapestry - Coach, Kate Spade, and Stuart Weitzman

Manager, Data Science Analytics

Reposted 18 Days Ago

Hybrid

New York, NY, USA

110K-130K Annually

Senior level

110K-130K Annually

Senior level

eCommerce • Fashion • Other • Retail • Sales • Wearables • Design

The Manager of Data Science Analytics will leverage advanced analytics to drive growth for Tapestry's brands by collaborating with cross-functional teams, performing large-scale analyses, and implementing data-driven strategies.

Top Skills: BigQueryETLGoogle AnalyticsPythonRSQLTableau

MetLife

Marketing Data Engineering Lead

19 Days Ago

Hybrid

Cary, NC, USA

Senior level

Fintech • Information Technology • Insurance • Financial Services • Big Data Analytics

Lead the development of scalable data solutions in Azure, oversee data integration for marketing analytics, and optimize data architecture and governance.

Top Skills: Azure Data FactoryAzure DatabricksAzure FunctionsAzure Synapse AnalyticsPowershellPythonScalaSparkSQL

CNA

Data Analytics Senior Consultant - Portfolio Management

19 Days Ago

Hybrid

72K-141K Annually

Senior level

72K-141K Annually

Senior level

Cloud • Insurance • Professional Services • Analytics • Cybersecurity

The Data Analytics Senior Consultant will create automated scorecards and scenario analysis tools for underwriting strategies. They will leverage analytical and technical skills to drive significant business impact, collaborate with senior underwriting leadership, and utilize various data sources to provide insights for decision-making. The role involves managing multiple projects and providing guidance to less experienced colleagues in a dynamic environment.

Featured Jobs

Cash App

Senior Data Scientist, Banking Core

Featured

Remote

Hybrid

PwC

Media & Entertainment Data Analytics & Reporting - Manager

Featured

Hybrid

Los Angeles, CA, USA

Zocdoc

Director, Data & Analytics Engineering

Featured

Hybrid

New York, NY, USA

Dotdash Meredith

Manager, Campaign Analytics

19 Days Ago

Hybrid

New York, NY, USA

Senior level

AdTech • Consumer Web • Digital Media • eCommerce • Marketing Tech

The Manager of Campaign Analytics will drive data analytics for digital campaigns, focusing on analysis, performance measurement, and actionable insights for revenue growth. This role involves managing a small team, collaborating on analytics strategies, and creating deliverables for high-priority finance accounts. Responsibilities also include leading analytics projects and mentoring direct reports.

Thrive Market

Manager, Data Engineering & Applications

21 Days Ago

Remote

150K-200K Annually

Senior level

150K-200K Annually

Senior level

Consumer Web • eCommerce • Food • Healthtech • Natural Language Processing • Social Impact

Lead data engineering and system integration initiatives, ensuring high data quality and operational effectiveness. Collaborate with stakeholders to deliver technical solutions and build effective teams.

Top Skills: Apache AirbyteApache AirflowApache NifiBoomiCensusDbtDebeziumFivetranHightouchKafkaMulesoftPythonRabbitMQSQLTalendWorkato

iLending

Director of Data Engineering and Analytics

Reposted 21 Days Ago

Englewood, CO, USA

145K-165K Annually

Senior level

145K-165K Annually

Senior level

Automotive • Financial Services

As the Director of Data Engineering and Analytics at iLending, you will oversee all data management and analytics activities, perform in-depth analyses to identify strategic opportunities, and manage data infrastructure using tools like SQL and Tableau. You will collaborate with various departments to drive data-informed decision-making and cultivate a data-driven culture within the organization.

Top Skills: AnalysisAWSAzureConsumer LendingData InfrastructureData ManagementData ModelingData Visualization ToolsEtl ProcessesExcelSQLStrategic InsightsTableau

NinjaTrader

Sr. Director of Data, Analytics and AI

21 Days Ago

Easy Apply

Hybrid

Chicago, IL, USA

Easy Apply

Senior level

Fintech • Financial Services

The Sr. Director of Data, Analytics, and AI will lead the data infrastructure, data science, business intelligence, and AI initiatives at NinjaTrader. Responsibilities include managing a high-performing team, establishing data governance, partnering with business functions for data-centric decision-making, and developing interactive dashboards.

Pfizer

Senior Director, Statistics Lead

Reposted 23 Days Ago

Hybrid

Collegeville, PA, USA

191K-341K Annually

Senior level

191K-341K Annually

Senior level

Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical

Lead biostatistical components for drug development, providing statistical expertise, guidance, and innovative methodologies. Collaborate on complex clinical projects and enhance internal statistical capabilities.

Top Skills: Clinical DataMathematical ModellingStatistical ComputingStatistical Theory

NBCUniversal

Lead Engineer of Data Quality & Applied Research - Data Engineering, Peacock

24 Days Ago

Hybrid

New York, NY, USA

130K-170K Annually

Senior level

130K-170K Annually

Senior level

AdTech • Cloud • Digital Media • Information Technology • News + Entertainment • App development

The Lead Engineer of Data Quality & Applied Research oversees data quality solutions, manages a team of engineers, and drives innovation using modern technologies like Generative AI. Responsibilities include developing data quality monitors, supporting data operations, leading experimental projects, and promoting best practices across the data organization.

Top Skills: Apache AirflowSparkGenerative AiJavaMachine LearningNatural Language ProcessingPythonRScalaSQL

Cargill

Sr. Director, AI & Data Science (Hybrid, Atlanta - Midtown)

Reposted 24 Days Ago

Atlanta, GA, USA

Senior level

Food • Greentech • Logistics • Sharing Economy • Transportation • Agriculture • Industrial

The Sr. Director of AI & Data Science leads the development and implementation of AI solutions that drive strategic decision-making. The role involves building relationships with leaders, guiding product delivery, improving AI practices, and ensuring measurable outcomes while managing risks and team performance.