Top Senior Level Data Engineer Jobs

As a Senior Database Engineer at Strava, you will work on infrastructure tools to enhance the platform's reliability and scalability. Responsibilities include developing automated solutions, migrating databases, and supporting engineering teams to boost product development efficiency. You will also be involved in enhancing disaster recovery and contributing to the Kubernetes ecosystem.

The Head of Data Science & Analytics will lead the data science team, manage strategic projects, develop innovative solutions, and collaborate with cross-functional teams to optimize processes and enhance products and services using data-driven strategies.

As a Senior Data Engineer at Egen, you will design and develop GCP data pipelines, maintain documentation, collaborate with teams for technical design specs, and lead initiatives for data-driven decision-making in healthcare. The role requires strong technical proficiency in Google Cloud tools and SQL.

The Senior Data Architect will design and support the corporate master data program, ensuring data integrity and governance. Responsibilities include implementing data strategies, managing data architectures, leading the design of data warehouses, and defining governance policies to enhance operational efficiency and reporting.

Design and implement infrastructure for training, evaluating, and deploying deep learning models for self-driving semi trucks. Develop and optimize training pipelines, track metrics, and enable continuous integration and deployment of model improvements in collaboration with cross-functional teams.

As a Senior Data Analyst, you will transform raw data into valuable information using analytics applications. Collaborate with stakeholders and the product development team to analyze requirements, prepare documentation, and evaluate product performance. Your expertise in Business Intelligence and Data Analytics will drive solutions and improvements.

As a Staff Data Engineer at 2K, you will focus on designing and building data models for Data Science and Business Intelligence, constructing APIs and data products, monitoring data pipelines, and collaborating with business partners and developers to ensure requirements are met for various initiatives.