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Top Remote Senior Level Data Engineer Jobs in Boise, ID
As a Senior Machine Learning & Computer Vision Engineer at Dandy, you will build advanced models for 3D scans, research state-of-the-art methods for generative deep learning, and collaborate with cross-functional teams to enhance product offerings. Your role involves working with large datasets, implementing MLOps best practices, and innovating new solutions in a growing team environment.
The Senior Data Engineer will design, develop, and maintain data pipelines and infrastructure, focusing on optimizing data for AI/ML models. Responsibilities include leading the creation of data warehouses, ensuring data quality, and collaborating with cross-functional teams to meet data requirements for machine learning applications.
The Director of Consumer Insights & Data Analytics will optimize customer behaviors and improve the purchase journey using data insights. Responsibilities include leading research, analyzing user behavior, driving marketing activities, and developing tools for measuring brand strength and customer segmentation.
The Presales Data Principal will work to understand client needs and design effective data solutions using SaaS technologies like Snowflake and Databricks. Responsibilities include technical storytelling, responding to RFPs, and leading all aspects of pre-sales processes. The role emphasizes interpersonal skills, deal conversion, and guiding clients on data best practices and AI/ML capabilities.
As a Staff Data Engineer, you will design and implement scalable data solutions, optimize data infrastructure, and support BI product development. You will collaborate with stakeholders for project alignment and success while managing data workflows and governance tools.
The Senior Data Engineer will develop and scale a high-traffic digital ad exchange, mentor junior engineers, implement software best practices, and contribute to the architectural strategy. Responsibilities include shipping features, optimizing performance, and enhancing the overall platform.
As the Director of Data Science & AI, you will lead a team to develop AI and ML solutions that align with the business strategy. Responsibilities include overseeing the ML workflow, collaborating with Product and Engineering, and managing a high-performance team to drive customer-centric analysis and strategic initiatives.
The Data & Analytics Solution Architect at MCA Connect leads project implementations, mentors junior teammates, and drives continuous improvement. They design and implement data solutions using Microsoft technologies in Azure and On-Prem, ensuring projects are within budget and timeline while communicating with stakeholders.
The VP of Data Engineering at Axios leads the data engineering functions, overseeing teams for Data Engineering, Data Science, and Data Analytics. Responsibilities include managing data architecture, strategy development, technical guidance, team roadmaps, and maintaining best practices across departments. This executive role collaborates with stakeholders, fosters an inclusive team environment, and supports the overall mission of delivering trustworthy news content.
The Senior Data Engineer will develop technical plans for data migration involving ingestion, transformation, storage, and access control primarily using Azure. Responsibilities include ensuring data quality, implementing robust data validation, and providing technical guidance to teams while keeping up with advancements in data engineering technologies.
The Senior Data Engineer will be responsible for developing technical migration plans, building scalable data ingestion frameworks, ensuring data quality, and providing technical guidance during the migration process. Collaboration with cross-functional teams to deliver high-quality solutions in various business domains is essential.
The Senior Data Engineer will work with the BAI team to develop data solutions, overseeing data migration and management, ensuring data quality, using Azure's Data Factory, and providing technical guidance. The role requires collaboration with cross-functional teams to address challenges in various domains including supply chain and finance.
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