Solution Architect - Qualified Pipeline

Data Meaning; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

A leading consulting firm in the realm of Business Intelligence and Data Analytics seeks a skilled Solutions Architect. In this pivotal role, you will drive the design of innovative cloud-based data architectures that meet the intricate needs of clients while fostering a collaborative and inclusive virtual environment. With 10+ years of specialized experience, you will guide both internal teams and customers in crafting efficient, secure, and scalable data infrastructures.

Qualifications

• 10+ years of experience designing data architectures.
• Strong focus on cloud platforms (Azure, AWS).
• Certifications preferred in cloud data platforms.

Responsibilities

• Design and implement advanced data strategies.
• Collaborate on architecture diagrams and data models.
• Provide technical expertise in cloud environments.

Skills

Cloud data platforms expertise

Data architecture design

Communication skills

Problem-solving

Analytical thinking

Team collaboration

Tools

Azure

AWS

Snowflake

Synapse

Databricks

Job description

• 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 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:

• 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.

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