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Data Platform Architect Jobs (NOW HIRING)

Prolim Global

Platform Architect

San Francisco, CA · On-site

Key Responsibilities Data Architecture & Solution Design * Architect and design scalable, secure, and high-performance data platforms using Palantir Foundry. * Develop data architectures supporting ...

Troon

AI Platform Architect

Scottsdale, AZ · On-site

The AI Platform Architect designs and implements the architecture that connects Troon's data platform to AI-enabled applications, including retrieval-augmented generation (RAG) services, document and ...

Troon Golf

AI Platform Architect

Scottsdale, AZ · On-site

The AI Platform Architect designs and implements the architecture that connects Troon's data platform to AI-enabled applications, including retrieval-augmented generation (RAG) services, document and ...

CFS

Platform Architect

Madison, WI · Hybrid

$155K/yr

Design reference architectures and standards for microservices, serverless, data platforms, and ... Architect shared platform capabilities such as landing zones, internal developer platforms, and ...

Koantek

Databricks Platform Architect

Chandler, AZ · On-site

Lead Data Platform Architect / Data bricks Migration Lead Location: Remote Position Type: Contract Job Overview We are seeking an accomplished, technology-driven Lead Data Platform Architect ...

Koantek

Databricks Platform Architect

Chandler, AZ · Remote

Lead Data Platform Architect / Data bricks Migration Lead Location: Remote Position Type: Contract Job Overview We are seeking an accomplished, technology-driven Lead Data Platform Architect ...

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Data Platform Architect information

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How much do data platform architect jobs pay per hour?

As of Jun 14, 2026, the average hourly pay for data platform architect in the United States is $69.98, according to ZipRecruiter salary data. Most workers in this role earn between $61.30 and $78.85 per hour, depending on experience, location, and employer.

How much does a platform architect make?

A Data Platform Architect typically earns between $100,000 and $160,000 annually, depending on experience, location, and industry. Senior roles with specialized skills in cloud platforms and data management tools can command higher salaries, often exceeding $180,000.

How much money do data architects make?

Data architects typically earn a median annual salary between $100,000 and $150,000, depending on experience, location, and industry. Senior roles with specialized skills in cloud platforms and data modeling can exceed $160,000 annually.

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

To thrive as a Data Platform Architect, you need deep expertise in data modeling, database design, cloud platforms, and related technologies, typically supported by a degree in computer science or a related field. Familiarity with tools like Azure, AWS, Google Cloud, ETL systems, and certifications such as AWS Certified Solutions Architect or Microsoft Certified: Azure Data Engineer are highly valued. Strong problem-solving, project management, and communication skills help you collaborate effectively with engineers and stakeholders. These competencies are vital for designing scalable, secure, and efficient data architectures that meet organizational needs.

What is a Data Platform Architect?

A Data Platform Architect is a professional responsible for designing and overseeing the development of a robust data infrastructure within an organization. They create scalable architectures that support data collection, storage, integration, and analysis, ensuring that data flows securely and efficiently across systems. This role requires expertise in cloud services, databases, data modeling, and data governance to help businesses make informed decisions based on reliable data. Data Platform Architects often collaborate with data engineers, analysts, and business leaders to deliver solutions that support analytics, reporting, and digital transformation initiatives.

What are some common challenges Data Platform Architects face when designing scalable data solutions?

Data Platform Architects often encounter challenges such as ensuring system scalability to handle rapidly growing data volumes, integrating disparate data sources, and maintaining data quality and security across platforms. Balancing the need for real-time data access with cost-effective storage and compute resources can also be demanding. Collaboration with data engineers, analysts, and business stakeholders is crucial to align technical solutions with organizational goals and to ensure the platform supports evolving business needs.

What does a data platform architect do?

A data platform architect designs and oversees the infrastructure that supports data collection, storage, processing, and analysis within an organization. They evaluate and implement technologies such as cloud services, data warehouses, and data pipelines, ensuring systems are scalable, secure, and efficient. Strong knowledge of data modeling, architecture principles, and tools like SQL, Hadoop, or Spark is essential for this role.

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

AspectData Platform ArchitectData Engineer
CredentialsTypically requires a bachelor’s degree in computer science, data management, or related fields; certifications like AWS Certified Data Analytics or Google Cloud Professional Data Engineer are common.Requires similar degrees and certifications, often including cloud platform certifications and programming skills.
Work EnvironmentFocuses on designing and overseeing data infrastructure, working closely with architects, stakeholders, and development teams.Builds, maintains, and optimizes data pipelines and databases, often working directly with data warehouses and ETL processes.
Industry UsageUsed across industries to develop scalable data platforms and strategies.Commonly employed in data integration, processing, and pipeline development roles.

While both roles require strong technical skills and knowledge of data systems, the Data Platform Architect primarily designs the overall data infrastructure, whereas the Data Engineer focuses on building and maintaining data pipelines. They often collaborate closely to ensure a robust data environment.

How much does a data architect get paid?

Data architects typically earn a salary ranging from $100,000 to $160,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in cloud platforms and data modeling can command higher compensation.
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Data Platform Architect jobs near you
Infographic showing various Data Platform Architect job openings in the United States as of June 2026, with employment types broken down into 71% Full Time, and 29% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $145,556 per year, or $70 per hour.
Principal Data Platform Architect

Principal Data Platform Architect

Ventura Foods

Irvine, CA • Hybrid

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted yesterday

Ventura Foods rating

6.9

Company rating: 6.9 out of 10

Based on 32 frontline employees who took The Breakroom Quiz

205th of 383 rated food and drinks producers

Job description

Employment Type: Salaried
Work Arrangement: Hybrid 

Position Summary:

The Principal Data Platform Architect defines and drives the company’s enterprise data platform strategy and roadmap. This role designs a modern lakehouse architecture on Snowflake, enables self-service BI, advances integration across systems and data domains, and establishes the foundation for machine learning and AI platforms—ensuring the ecosystem is scalable, secure, and delivers trusted data for business value.

Major Duties and Responsibilities:
  • Define and own the enterprise data platform strategy and roadmap:
    -Develop the architectural vision for data, integration, analytics, and AI platforms.
    -Align platform capabilities with evolving business needs such as growth, efficiency, compliance, and innovation.
    -Establish architectural principles, standards, and governance.
  • Design and govern Snowflake-based lakehouse architecture (medallion model):
    -Design the logical data models for bronze, silver, and gold layers.
    -Ensure data quality, lineage, and security across structured and semi-structured data.
    -Optimize performance, cost management, and multi-tenant scalability.
  • Lead integration architecture across systems and data domains:
    -Define patterns for API-led, event-driven, and batch data movement.
    -Standardize error handling, monitoring, and metadata capture.
    -Ensure interoperability between enterprise applications, data warehouse, and operational platforms.
  • Enable and expand self-service BI and analytics:
    -Architect semantic layers and governed datasets for analytics platforms.
    -Define policies for certified vs. exploratory analytics.
    -Deliver frameworks for data catalogs, data dictionaries, and end-user guides.
  • Lay the foundation for machine learning and AI platforms:
    -Ensure data pipelines support ML feature engineering and model training.
    -Partner with data science teams to establish MLOps best practices.
    -Enable reuse of data assets for predictive and generative AI use cases.
Education and Experience:

Education

  • Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field required.
  • Master’s degree in Computer Science, Information Management, or Business/Technology discipline preferred.

Experience

  • 10+ years of experience in data architecture, data engineering, or enterprise data platforms.
  • 5+ years in a senior/lead architect role driving platform strategy, standards, and governance at enterprise scale.
  • Proven expertise designing and operating cloud-based data platforms (Snowflake or similar), including lakehouse/medallion architectures.
  • Hands-on experience with ELT/ETL tools, data modeling, and metadata management (dbt, Fivetran, or comparable).
  • Strong background in enterprise integration (API-led, event-driven, or batch patterns).
  • Demonstrated success enabling self-service BI and analytics platforms with governed semantic layers.
  • Exposure to machine learning/AI platforms and MLOps practices for operationalizing models.
  • Track record of partnering with business leaders to align data platforms with strategic business needs (growth, efficiency, compliance, innovation).
  • Excellent leadership, communication, and stakeholder management skills; experience influencing technical and executive audiences.
Knowledge and Skills:
  • Data Architecture & Modeling – Expert in designing lakehouse architectures (bronze/silver/gold) and enterprise data models that support both analytics and AI/ML workloads.
  • Cloud Data Platforms – Deep hands-on knowledge of Snowflake (or equivalent cloud-native platforms), including performance tuning, cost optimization, multi-tenant design, and governance.
  • Data Engineering & ELT – Strong proficiency in dbt or similar transformation frameworks, ELT/ETL orchestration, metadata management, and automation of data pipelines.
  • Integration Patterns – Advanced understanding of API-led, event-driven, and batch integration; skilled at designing reusable integration frameworks.
  • Analytics & BI Enablement – Skilled at architecting self-service BI environments, semantic layers, and governed datasets; experience with enterprise BI tools.
  • Machine Learning & AI Enablement – Familiarity with ML pipelines, feature stores, and MLOps practices to operationalize AI models.
  • Security, Compliance & Governance – In-depth knowledge of data security, privacy, and governance frameworks, including RBAC/ABAC models and regulatory compliance.
  • Leadership & Communication – Strong ability to translate complex technical concepts into business value, influence senior executives, and guide cross-functional teams.
  • Strategic Thinking – Ability to balance long-term platform vision with short-term delivery, ensuring scalability, adaptability, and cost-effectiveness.

Why Join Us:
Ventura Foods innovates and manufactures food solutions for foodservice and retail businesses.  We make exclusive products for the world's most iconic restaurants and retailers, we provide ready-to-go product solutions for professional kitchens, and we make consumer brands everyone knows and loves.  When you work for Ventura Foods, you get a strong foundation of training, a manager who cares about you and celebrates your success, a safe environment, and challenging work.  As part of our team, your future is limited only by how much you’re willing to push yourself to get there. We invest in your growth because you invest in ours.  

Ventura Foods offers career growth opportunities as well as competitive compensation and benefits:​

  • Medical, Prescription, Dental, & Vision – coverage beginning on your 1st day for eligible employees​
  • Profit Sharing and 401(k) matching (after eligible criteria is met)​
  • Paid Vacation, Sick Time, and Holidays​
  • Employee Appreciation Events​ and Employee Assistance Programs
  • Salary Base Range of $150,000 - $185,000*

*The “base salary range” provided above is a good faith estimate of what we expect to pay for this position in the specified markets.  Ventura Foods reserves the right to pay outside of the given range based on a variety of factors including but not limited to: candidate skills and experience, complexity of the job, budgetary factors, and location/geography.  Ventura Foods conducts regular reviews of compensation ranges and therefore reserves the right to alter this range at any given time.  

Diversity & Inclusion:
Our commitment to a diverse and inclusive environment in which all employees are treated with respect is evident in our company culture and values.  We believe that fostering an environment of inclusion and a focus on diversity across our organization is vital to attracting top talent, driving innovation, and meeting the high expectations of our customers in a rapidly evolving global marketplace.

Ventura Foods is proud to be an equal opportunity employer.  All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, disability status, protected veteran status or any other characteristic protected by law.

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