Top Data Engineer Jobs in Palm Bay-Melbourne-Titusville,
As a Senior Data Engineer at Dandy, you will design and maintain data infrastructure, own end-to-end data pipelines, and collaborate with stakeholders to ensure reliable data solutions. You'll mentor junior engineers and continuously improve systems to enhance data-driven decision-making across the organization.
The Data Architect Manager at PwC will design and develop robust data solutions, transform raw data into actionable insights, and lead projects in data engineering. Responsibilities include developing data pipelines, mentoring team members, collaborating on data strategies, and ensuring compliance with data governance policies.
As a Data Engineering Manager at PwC, you will lead the design and implementation of data solutions, manage team performance, and enhance data architecture strategies. Your role involves developing data pipelines, integration, and transformation solutions while mentoring team members. You will ensure projects meet quality standards and collaborate with stakeholders to address data requirements, all while upholding PwC values and professional standards.
As a Cloud Data & Analytics Senior Manager, you will assist clients in devising cloud data strategies, selecting suitable platforms, and migrating to modern cloud environments. Your role encompasses dealing with unstructured problems, leading teams, engaging with stakeholders, and contributing to technical solutions using various cloud technologies.
As a Senior Machine Learning Engineer, you will design data pipelines, develop machine learning models, and collaborate with various teams to integrate ML capabilities into products. You will also train others, conduct experiments to validate outcomes, and serve as a thought leader in data-driven innovations.
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The Senior Data Engineer will design and architect data pipelines and ETL processes, maintain data lakehouse solutions, optimize data strategies across cloud platforms, mentor junior engineers, and ensure the high availability of data infrastructure while collaborating with data scientists for advanced analytics initiatives.
The Vice President of Business Development will drive growth in the Data & AI practice by developing go-to-market strategies, qualifying and closing multi-year engagements, and leveraging relationships with platform partners and sales professionals. This role focuses on data modernization, analytics, digital transformation, and implementing data-driven solutions.
As a Senior Data Engineer at Arcadia, you will develop solution architecture, automate data pipelines connecting client claim and clinical data platforms with our health solution platform, and contribute to improving data integration tools. You will participate in scrum ceremonies, code reviews, and manage multiple implementations simultaneously.
Empower seeks an experienced analytics leader to oversee Credit and Data Science functions for international markets in Latin America and South East Asia. The role includes developing risk models, launching innovative products, and understanding consumer behaviors to drive business growth and improve customer financial well-being.
As a Data Science Co-op at Jellyfish, you will help develop algorithms, create machine learning models, and analyze data to provide insights for engineering teams. You will collaborate with customers and contribute to marketing efforts while exploring applied mathematics and machine learning.
As a Principal Full Stack Engineer, you'll lead the design and integration of ad analytics and ad fraud products, manage the software development lifecycle, mentor junior engineers, and ensure best practices in a collaborative environment. You'll work with product teams to gather requirements, build scalable systems, and automate cloud infrastructure.
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As a Senior Machine Learning Engineer at Wasabi, you will develop and refine computer vision algorithms and NLP models while leading AI advancements in a team-oriented environment. Responsibilities include collaborating across teams, optimizing machine learning models, and ensuring reliable implementation and maintenance of AI systems.
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