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Data Solutions Architect Jobs (NOW HIRING)

Enterprise Data Solution Architect Atlanta, GA(Remote) Full-time role Skills Required: ADF(Azure Data Factory); Databricks; Python; SQL and Azure cloud JD: Required Skills & Qualifications:

Data Solutions Architect Location: Seattle, WA Role Overview: You are the technical backbone of the data ecosystem. You will design and implement the robust, scalable environments required to move ...

Who We're Looking For - Reporting to the VP of Strategy, Insights & Analytics , we are seeking a Data Solutions Architect to serve as the primary architect and guardian of our enterprise data ...

Who We're Looking For - Reporting to the VP of Strategy, Insights & Analytics , we areseeking a Data Solutions Architect to serve as the primary architect and guardian of our enterprise data ...

... data architecture of the General Sessions Data Repository, in collaboration with data users, court personnel, IT teams, and other stakeholders within the AOC. ยท Create short-term tactical solutions ...

OTSI (Object Technology Solutions, Inc) has an immediate opening for an AI & Data Solutions Architect Location: Seattle (Remote, some travel required) We are seeking a highly technical, client-facing ...

OTSI (Object Technology Solutions, Inc) has an immediate opening for an AI & Data Solutions Architect Location: Seattle (Remote, some travel required) We are seeking a highly technical, client-facing ...

Senior Data Solutions Architect Location: U.S. - Remote - East Coast Hours Employment Type: Full-Time / Direct Hire Work Authorization: Must be authorized to work in the U.S. without sponsorship (U.S.

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How much do data solutions architect jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for data solutions architect in the United States is $71.23, according to ZipRecruiter salary data. Most workers in this role earn between $64.90 and $80.05 per hour, depending on experience, location, and employer.

How do Data Solutions Architects typically collaborate with cross-functional teams during large-scale data projects?

Data Solutions Architects play a pivotal role in bridging gaps between data engineers, business analysts, and stakeholders during large-scale projects. They translate business requirements into technical solutions, ensuring alignment between architecture strategies and organizational goals. Regular collaboration occurs through design sessions, code reviews, and project meetings, where they provide expertise on data modeling, integration, and system scalability. This collaborative environment helps ensure that data solutions are robust, scalable, and meet both technical and business needs.

What is a Data Solutions Architect?

A Data Solutions Architect is a professional responsible for designing, building, and overseeing data solutions that support business needs. They create the technical blueprint for how data is collected, stored, integrated, and accessed across an organization. Their work involves choosing appropriate technologies, ensuring data quality and security, and aligning data systems with business goals. Data Solutions Architects often collaborate with data engineers, analysts, and other stakeholders to deliver scalable and efficient data infrastructures.

What is the difference between Data Solutions Architect vs Data Engineer?

AspectData Solutions ArchitectData Engineer
Required CredentialsBachelor's/Master's in CS, certifications like AWS, AzureBachelor's in CS, certifications like Hadoop, Spark
Work EnvironmentDesigning data solutions, collaborating with stakeholdersBuilding and maintaining data pipelines, coding
Employer & Industry UsageTech, finance, healthcare, consultingTech companies, data-driven organizations
Search & Comparison IntentUnderstanding strategic data roles, designing solutionsTechnical implementation, data pipeline development

The Data Solutions Architect focuses on designing comprehensive data solutions and aligning them with business needs, often working closely with stakeholders. In contrast, Data Engineers primarily build and maintain the data infrastructure and pipelines. Both roles require technical skills and certifications but differ in scope and responsibilities within data teams.

What are the key skills and qualifications needed to thrive as a Data Solutions Architect, and why are they important?

To thrive as a Data Solutions Architect, you need expertise in data modeling, database design, and systems integration, typically supported by a degree in computer science or a related field. Familiarity with cloud platforms (such as AWS, Azure, or Google Cloud), data warehousing tools, and relevant certifications like AWS Certified Solutions Architect are highly valuable. Strong problem-solving, communication, and stakeholder management skills help you translate business needs into scalable technical solutions. These skills ensure that data architectures are robust, secure, and aligned with organizational goals.
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What cities are hiring for Data Solutions Architect jobs? Cities with the most Data Solutions Architect job openings:
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Infographic showing various Data Solutions Architect job openings in the United States as of May 2026, with employment types broken down into 28% Full Time, 55% Part Time, and 17% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $148,157 per year, or $71.2 per hour.
Data Solutions Architect

Full-time

Posted 8 days ago


Job description

Enterprise Data Solution Architect
Atlanta, GA(Remote)
Full-time role
Skills Required: ADF(Azure Data Factory); Databricks; Python; SQL and Azure cloud
JD:
Required Skills & Qualifications:
  • Bachelor's or Master's degree in related field.
  • Experience in data engineering or architecture roles, with working specifically on Azure data solutions.
  • Experience as a Solutions Architect.

Expertise in:
  • Azure Data Factory (ADF) - Pipelines, Dataflows, Integration Runtime
  • Azure Databricks.
  • Proficiency in SQL for querying, data modeling, and tuning.
  • Experience with Python, PySpark, or Scala in Databricks environments.

Preferred / Nice to Have:
  • Hands-on experience with Power BI - developing dashboards, DAX, and data modeling.
  • Strong understanding of data governance, security, and metadata management.