Data Architect - Senior Data Architect

Vaga não está no LinkedIn

🕒 Julho 2, 2025

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $150.000 - $190.000 / ano

⏰ Tempo Integral

🟠 Sênior

🚰 Engenheiro de Dados

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Innovative Solutions

SiteLinkedInTodas as Vagas

51 - 200 funcionários

☁️ SaaS

🤖 Inteligência Artificial

Cloud • SaaS • Artificial Intelligence

A Innovative Solutions é um provedor de soluções de TI completo que se especializa em ajudar empresas a aproveitarem o poder da nuvem para impulsionar o crescimento. Como parceiro de serviços de nível Premier da AWS, a Innovative Solutions oferece uma gama de serviços, incluindo migrações para a nuvem da AWS, Serviços Gerenciados, IA Generativa, Modernização de Aplicações e Operações em Nuvem. A empresa está comprometida em transformar sistemas de TI para apoiar estratégias de crescimento empresarial, com foco em fornecer soluções personalizadas que melhoram a aquisição e retenção de clientes, enquanto aumentam a lucratividade. Com mais de 120 certificações AWS e uma equipe 100% certificada em nuvem, a Innovative Solutions enfatiza serviços personalizados e focados no cliente para alcançar uma alta taxa de retenção de clientes.

Descrição

• As a Cloud Architect on our Professional Services team, you will be responsible for designing, implementing, migrating to, and managing clients' data-driven cloud architectures and infrastructure using AWS. • You will work alongside team members to help migrate customer data systems to the cloud, build and optimize data pipelines and analytics solutions, architect scalable data platforms, recommend data technologies and storage solutions to meet client needs, contribute to data engineering R&D initiatives, and mentor team members on data architecture best practices. • Responsible for: • Creating, implementing, and maintaining cloud architecture for clients • Migrating systems to hybrid or cloud-based solutions • Troubleshooting and optimizing clients’ cloud infrastructure • Working with developers to support and maintain application lifecycles • Assisting with design and implementation of new cloud architecture that follow best practice guidelines • Working with Project Managers and clients to provide recommendations and technology roadmaps to meet their business needs • Actively participating in team meetings and cross-functional interactions • Keeping team members and supervisors informed of progress and issues • Actively contributing in client project status meetings • Contributing to R&D projects to validate/invalidate new services offerings • Mentoring and guiding members of the delivery team in a technical and non-technical capacity • Remaining current with technology trends and new technologies • Proposing latest technology usage and integration standards • How you will be successful: • Living and breathing the “cloud-first” approach • Having a high degree of analytical thinking capability to solve complex business problems • Obsessively delivering amazing customer experiences • Becoming a subject matter expert in one or more cloud platforms in 9-12 months • Building trusting relationships with team members and collaborating departments • Comfortable with pushing boundaries and technical limits (maintain technical aptitude and knowledge of industry) • Always be learning

🎯 Requisitos

• 5+ years professional IT experience • 2+ years professional AWS or Azure experience • At least (1) AWS or Azure Certification (professional level) • Programming languages like Python, R, Java, Scala etc. to build data pipelines, perform data analysis and create machine learning models. • SQL and NoSQL databases like PostgreSQL, MySQL, MongoDB, Cassandra etc. to store and query large datasets. • Data modeling skills - ability to design conceptual, logical and physical data models. • Understanding of dimensional modeling, star schemas, data warehouses. • ETL (Extract, Transform, Load) tools like Informatica, Talend, Pentaho etc. to integrate and move data between systems. • Big data frameworks like Hadoop, Spark, Kafka etc. for distributed data processing and building data lakes • Machine learning frameworks like Tensorflow, PyTorch, Keras, Scikit-Learn for building ML models. • Knowledge of data architecture patterns like lambda, kappa architecture. Ability to design scalable and flexible data pipelines.