Top Senior Data Management Jobs in Austin, TX

The Digital Ops Data Manager ensures the right data architecture for tracking and analytics integration, manages data assets, and collaborates with multiple teams.

The Analytics Manager will lead a team of analysts, focusing on data product delivery in the life insurance sector, while ensuring quality standards and mentoring team members.

The Manager, Data Operations leads a team of analysts, solving complex data problems, ensuring data quality, improving existing processes, and overseeing daily performance to enhance data-driven decision-making.

Lead the development of analytics solutions across operations, manage a team of analysts, and drive operational excellence and decision-making through data insights.

Responsible for managing all data management activities for clinical studies, including data collection, cleaning, reporting, and validation, while ensuring regulatory compliance and quality data delivery.

Lead a team of data scientists to develop marketing mix and attribution models, providing insights on marketing performance and optimizing investments across products and channels.

Lead architect for Compliance data at Coinbase, defining data governance frameworks, designing data contracts, mapping data lineage, and quantifying data impact to enhance compliance reporting and data quality processes.

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.

The Senior Analytics and Insights Manager partners with GTM teams to drive data-driven decisions, providing insights, KPIs, and fostering collaboration for improved performance and strategy execution.

Lead external data strategy for global credit markets: identify, evaluate, onboard, and optimize external and credit bureau data; lead data science projects and advanced modeling; ensure data governance and regulatory compliance; collaborate cross-functionally; negotiate vendor partnerships; and build and mentor a high-performing team to drive credit risk and product outcomes.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

The Manager of Data Science for Fraud Incidents will lead a team to analyze and mitigate fraud attacks, develop data models, and collaborate with cross-functional teams to enhance fraud analytics and reporting capabilities.

Lead clinical data review for studies, ensuring the interpretation of efficacy and safety data, and collaborating with cross-functional teams.

The Manager of Data Engineering will lead the data engineering team, oversee data pipeline design and implementation, manage data governance, and ensure data quality while driving team professional growth.

The Analytics Manager will lead the analytics team, optimize data processes, manage KPIs, and create data visualizations to influence business decisions.

The Data Manager will execute analytics, manage data sourcing and dashboards, streamline reporting, and provide insights for business improvement and performance measurement.

Manage and develop a team of Data Analysts, oversee analytics deliverables, partner with cross-functional teams to deliver insights, and implement BI tools.

Lead a team of Data Scientists and Analysts, developing AI and data-driven solutions, driving analytics insights, and fostering collaboration across teams.

Lead development of provider data products and ML-based decision support, manage provider data quality, collaborate across teams to build provider-facing analytics, and establish MLOps standards and governance.

Manage a team of ~7 data scientists to deliver experimental design, product analytics, and actionable insights. Partner with product, engineering, and research to build measurement, data products, and reporting; ensure data accuracy, timely delivery, and best practices.

Lead a team of ~7 data scientists to deliver accurate product analytics and experimentation insights. Manage people, mentor staff, partner with product and engineering to build accessible data products, and improve measurement, reporting, and experiment practices to inform product decisions.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights. Manage people, partner with product and engineering, improve measurement and data products, and ensure rigorous large-scale analysis to inform product decisions.

Lead a Product Analytics data science team to deliver timely, accurate insights for product decisions. Manage ~7 data scientists, mentor teammates, partner with product and engineering, develop experimentation and measurement best practices, and build accessible data products and reports.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experiments; support product teams, build accessible data products, mentor staff, and improve measurement and reporting practices.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics: guide experimentation, partner with product and engineering, build accessible data products, mentor staff, and improve measurement and reporting practices to inform product decisions.