Solution Architect - Qualified Pipeline

DATA+; São Paulo; Teletrabalho; BRL 80.000 - 150.000; Tempo integral

Resumo da oferta

A forward-thinking company is seeking a Solution Architect to lead the development of advanced data strategies and architectures. In this role, you will collaborate with internal teams and clients to design scalable and secure data systems primarily on cloud platforms like Azure and AWS. The position emphasizes innovation and collaboration within a diverse, global team, ensuring high-quality standards and alignment with client objectives. If you are passionate about data architecture and eager to make an impact in a dynamic environment, this opportunity is perfect for you.

Qualificações

• 10+ years of experience in data architecture, focusing on cloud platforms.
• Strong expertise in cloud data platforms with preferred certifications.

Responsabilidades

• Design and implement data architectures aligned with client strategies.
• Provide technical expertise in data management for cloud environments.

Conhecimentos

Cloud Architecture

Data Management

Data Warehousing

ETL/ELT Processes

Communication Skills

Problem-Solving

Data Pipeline Design

Ferramentas

Azure

AWS

Snowflake

Databricks

Synapse

Descrição da oferta de emprego

Join to apply for the Solution Architect - Qualified Pipeline role at DATA+

Position Summary: Data Meaning is a front-runner in Business Intelligence and Data Analytics consulting, renowned for our high-quality consulting services throughout the US and beyond.

Our expertise lies in delivering tailored solutions in Business Intelligence, Data Warehousing, and Project Management.

We have a diverse, global team of consultants, all working remotely, embodying a collaborative, inclusive, and innovation-driven work culture.

As a Solution Architect at Data Meaning, you will be responsible for the development and implementation of advanced data strategies and architectures for our clients.

In this role, you will collaborate with both internal teams and customers to design scalable, efficient, and secure data systems, primarily on cloud platforms like Azure and AWS, ensuring they meet client needs and industry standards.

Responsibilities:

1. Collaborate with team members to design, develop, and implement modern data architectures that align with the customers’ business strategies and goals.
2. Contribute to the creation and maintenance of architecture diagrams, data models, and other key project deliverables.
3. Provide technical expertise in data management, ensuring data integrity, security, and optimal performance in cloud-based environments such as Azure, AWS, and Cloud Data Platforms (e.g., Snowflake, Synapse, Databricks).
4. Work closely with the sales team to formulate data solutions for prospective clients, assisting in the creation of project plans, timelines, and estimates.
5. Present technical solutions and project plans to customers, ensuring clarity and alignment with their business objectives.
6. Function as a senior technical resource during project implementation, ensuring alignment with client expectations and maintaining high-quality standards throughout the project lifecycle.
7. Participate in code and architecture reviews, ensuring data solutions adhere to high standards of performance, scalability, and maintainability.
8. Contribute to team and practice development by sharing knowledge, mentoring junior staff, and participating in continuous improvement initiatives.

Skills and Qualifications:

1. 10+ years of experience designing and implementing data architectures, with a strong focus on cloud-based platforms (Azure, AWS).
2. Strong expertise in cloud data platforms (Snowflake, Synapse, Databricks); certifications preferred.
3. Familiarity with data engineering best practices, including ETL/ELT processes, data lakes, and data warehousing.
4. Ability to work collaboratively in distributed teams across multiple geographies.
5. Outstanding communication skills with the ability to engage with both technical and non-technical stakeholders.
6. Strong problem-solving and analytical skills, with attention to detail in designing and implementing complex data systems.
7. Flexibility and adaptability to work in dynamic environments, managing multiple priorities and meeting tight deadlines.
8. Experience designing data pipelines that support AI/ML workloads, ensuring data is structured and processed for effective model training, evaluation, and deployment.