Solution Architect - Qualified Pipeline

Data Meaning; Brasil; Teletrabalho; BRL 180.000 - 250.000; Tempo integral

Resumo da oferta

A leading consulting firm in Brazil seeks a Solution Architect to develop and implement advanced data strategies for clients. You will collaborate with internal teams and customers while ensuring data integrity and security on cloud platforms like Azure and AWS. Ideal candidates have 10+ years of experience in data architecture with strong problem-solving skills and are flexible in dynamic environments.

Qualificações

• 10+ years of experience designing and implementing data architectures, focusing on cloud platforms.
• Certifications in cloud data platforms preferred.
• Ability to collaborate in distributed teams across geographies.

Responsabilidades

• Collaborate to design and implement modern data architectures.
• Ensure data integrity, security, and performance in cloud environments.
• Present technical solutions and project plans to customers.

Conhecimentos

10+ years of experience designing and implementing data architectures

Strong expertise in cloud data platforms (Snowflake, Synapse, Databricks)

Familiarity with data engineering best practices

Outstanding communication skills

Strong problem-solving and analytical skills

Flexibility and adaptability

Ferramentas

Azure

AWS

Snowflake

Databricks

ETL/ELT processes

Descrição da oferta de emprego

Long-term, Full-time position with Data Meaning

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 in Data Meaning you will develop and implement 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:

• Collaborate with team members to design, develop, and implement modern data architectures that align with the customers’ business strategies and goals.
• Contribute to the creation and maintenance of architecture diagrams, data models, and other key project deliverables.
• 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).
• Work closely with the sales team to formulate data solutions for prospective clients, assisting in the creation of project plans, timelines, and estimates.
• Present technical solutions and project plans to customers, ensuring clarity and alignment with their business objectives.
• Function as a senior technical resource during the implementation of projects, ensuring alignment with client expectations and maintaining high‑quality standards throughout the project lifecycle.
• Participate in code and architecture reviews, ensuring that data solutions adhere to high standards of performance, scalability, and maintainability.
• Contribute to team and practice development by sharing knowledge, mentoring junior staff, and participating in continuous improvement initiatives.

Skills and Qualifications:

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