Top Hybrid Data Engineer Jobs
The Principal Data Engineer will lead code development and manage data engineering solutions utilizing Python and SQL. Responsibilities include developing scalable applications on cloud platforms (AWS/GCP), maintaining databases, implementing search technologies, ensuring adherence to security practices, and training users while collaborating closely with cross-functional teams.
In this role, you will analyze and interpret data to create engaging narratives for media and clients. Responsibilities include producing data-driven articles, managing social media content, collaborating with data scientists, and generating story ideas that align with the company's business priorities.
The Data Engineer will join a data modeling team focusing on creating well-architected Data Cloud models for various industries. Responsibilities include designing, developing, and testing data models for analytical applications, collaborating with product teams, and improving data modeling practices. The role requires hands-on experience in data modeling and design.
As a Machine Learning Engineer, you will develop and deploy machine learning models to tackle complex business problems. Responsibilities include collaborating with cross-functional teams, analyzing data, optimizing models, and ensuring production-quality deployments while staying updated on machine learning advancements.
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In this role, you will lead various data and analytics projects, collaborating with client leaders to address business challenges using data-driven strategies. Responsibilities include designing and executing analytics strategies, mentoring junior staff, and supporting the growth of the consulting practice.
The Senior Consultant leads clients through transformational data and analytics strategies, collaborates with leaders to address business challenges, and contributes to consulting practice enhancement while managing teams on analytics initiatives.
As a Data and Analytics Senior Consultant, you will lead transformational change by designing and executing data and analytics strategies, collaborating with customers to address business challenges, and contributing to the growth of the consulting practice through exceptional service and business development.
The Machine Learning Engineer will collaborate with research scientists and partner laboratories to develop and improve end-to-end ML pipelines for multimodal models. The role involves training and serving robot foundation models while enhancing data infrastructure and contributing to significant publications.
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Lead a team of data scientists and engineers to develop innovative measurement products and data-driven solutions, ensure high-quality project delivery, and establish best practices for data science projects. Collaborate with multiple teams to enhance TV measurement and methodology while mentoring team members and advancing an inclusive culture.
The Principal Engineer will lead the Operations Analysis team to deliver analytical products guiding business strategy and product development. The role involves designing rigorous analyses, supporting requirements definitions and effectiveness studies for military operations, enhancing internal modeling and simulation capabilities, and presenting analytical findings to stakeholders.
The Data Engineer will collaborate with customers to understand their data management strategies, implement and optimize data solutions, design data architectures, and contribute to advanced analytics and machine learning implementations using AWS and IBM services. The role includes driving innovation and documenting data flows.
The Production and Data Specialist will oversee cultivation processes, manage inventory and sales data accuracy, generate reports for leadership, and support sales teams in customer account management. The role involves interdisciplinary collaboration to improve data management systems and processes regarding cannabis production and sales.
The Data Modeler will design, implement, and maintain data models, create reports and dashboards using analytics tools, collaborate with stakeholders, and ensure documentation and best practices are upheld. This role requires extensive experience in data modeling and analytics, particularly with Amazon Redshift, QuickSight, and Power BI, within the financial sector.
The Database Engineer will assist in the migration of on-prem databases to AWS and develop Infrastructure as Code (IaC) using Terraform and Gitlab. Responsibilities include performance tuning of Oracle databases, database environment monitoring, and collaborating on physical database design. The role involves independent work as well as teamwork within the financial services industry.
Top hybrid Companies Hiring Data + Analytics Roles
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