Data Engineering Manager

Drive strategy and delivery of scalable data platforms.

Provide technical leadership through architecture and design reviews.

Develop analytics capabilities across business units.

Improve development patterns and foundational datasets.

Define and execute data science strategy.

Lead AI/ML initiatives in healthcare/insurance.

Design and maintain marketing analytics data models.

Collaborate with cross-functional teams to define data needs.

Lead the centralized analytics function.

Develop and execute analytics vision and strategy.

Lead the company's analytics function.

Oversee data use cases and analytics platforms.

Define a research roadmap for strategic questions.

Lead quantitative research on user behavior.

Lead a team of product analysts.

Define and drive the analytical vision.

Lead and develop multiple data sub-teams.

Manage Data Lakehouse architecture and tooling decisions.

Design systems for product telemetry and analytics.

Ensure data reliability and scalability.

Lead the analytics engineering team to scale the data warehouse.

Mentor and provide feedback to junior engineers.

Design and maintain scalable data models.

Apply software engineering practices to analytics code.

Own end-to-end data architecture.

Build and manage batch data pipelines.

Lead and develop data teams.

Own and manage Data Lakehouse architecture.

Design and maintain data pipelines.

Optimize SQL queries and data models.

Provide data-driven insights for marketing strategy.

Measure impact of community and advocacy programs.

Lead and develop data teams.

Manage Data Lakehouse architecture.

Provide data-driven insights for marketing strategy.

Measure impact of community and advocacy programs.

Partner with teams for data-driven insights.

Develop scoring models for lead prioritization.

Collaborate with healthcare clients.

Translate data challenges into insights.

Provide data-driven insights for marketing strategy.

Measure community program impacts on adoption and pipeline.

Design and maintain data models.

Collaborate with teams for metric translation.

Build a self-service analytics system for the GTM team.

Integrate CRM, product usage, and marketing signals into a reporting model.

Provide data-driven insights for marketing strategies.

Measure impact of community and advocacy programs.

Lead and develop data engineering and analytics teams.

Manage the Data Lakehouse architecture and tooling decisions.

Transform questions into analytics recommendations.

Build models and conduct analyses for roadmap items.

Design and maintain scalable data pipelines.

Ensure data reliability, accuracy, and timeliness.

Design and maintain scalable data pipelines.

Write clean and well-documented code.

Provide data-driven insights for marketing strategy.

Measure impact of community and evangelism programs.

Build and lead the Data & ML team.

Own and manage the revenue data layer.

Lead and develop data teams.

Manage data architecture and tooling decisions.

Drive strategy and delivery of scalable data platforms.

Provide technical leadership through architecture and design reviews.

Provide data-driven insights for marketing strategy.

Measure impact of community and developer programs.

Provide data-driven insights to inform marketing strategy.

Establish proactive insights across the Marketing function.

Lead and develop data teams.

Manage Data Lakehouse architecture.

Lead the design and development of web applications.

Provide technical leadership and conduct reviews.

Lead the design and delivery of web applications.

Provide senior technical leadership and guidance.

Lead the Identity Frontend Pod.

Oversee frontend engineers working on identity flows.

Develop scalable and high-performance applications using Node.js and NestJS.

Collaborate with multidisciplinary teams to design and implement robust solutions.

Develop scalable backend systems for Open Banking.

Ensure secure and reliable integration of banking services.

Design and optimize scalable AI/ML models

Integrate AI solutions across business units

Design and optimize scalable AI/ML models

Integrate AI solutions across business units

Design and build software systems using relevant technologies

Develop integrations between core systems

Design and develop a cloud native API first platform for a Security Knowledge Platform™

Drive modernization efforts towards a reliable platform

Revolutionize enterprise data operations through AI solutions.

Automate and accelerate data tasks for overworked data teams.

Ensure reliability and scalability of blockchain infrastructure.

Automate deployments and operational processes across multi-cloud environments.

Architect cloud infrastructure solutions using Kubernetes and OpenStack

Integrate open source software like PostgreSQL and MongoDB

Enhance reliability of open source infrastructure

Automate operations for scalability

Transform education and productivity using the latest AI technologies

Develop tools for Goodnotes AI and foundational technologies

Transform education and productivity through AI technology

Build and maintain infrastructure for running end-to-end AI technology