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Data Analytics Architect Jobs in Texas (NOW HIRING)

Orion180

Data and Analytics Architect

Irving, TX · On-site

$61.25 - $78.75/hr

It also means evolving how we think about the role of a Data and Analytics Architect. The expectation isn't just technical execution. It's curiosity. Ownership. The ability to step into ambiguity ...

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All JobsData Analytics Architect JobsData Analytics Architect Jobs in Texas

Data Analytics Architect information

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$142.5K

$166.5K

$188.2K

How much do data analytics architect jobs pay per year?

As of Aug 1, 2026, the average yearly pay for data analytics architect in Texas is $166,533.00, according to ZipRecruiter salary data. Most workers in this role earn between $154,200.00 and $178,400.00 per year, depending on experience, location, and employer.

What are the typical career advancement opportunities for a Data Analytics Architect?

Data Analytics Architects often find excellent career growth opportunities within organizations, as their expertise in designing data frameworks is highly valued. With experience, many progress to senior or principal architect roles, chief data officer positions, or transition into broader leadership roles in data engineering or analytics strategy. Continuous learning and staying updated with emerging technologies, such as machine learning platforms and cloud-based analytics, also open doors to specialized roles. Working in this position exposes professionals to both technical challenges and business strategy, setting a strong foundation for advancement.

What are the key skills and qualifications needed to thrive in the Data Analytics Architect position, and why are they important?

A Data Analytics Architect requires strong expertise in data modeling, analytics platforms, and database management, often backed by a degree in computer science, information systems, or a related field. Familiarity with tools like SQL, Python, Spark, and cloud services (AWS, Azure, Google Cloud), along with certifications such as AWS Certified Data Analytics or Google Professional Data Engineer, is highly beneficial. Excellent problem-solving skills, communication abilities, and the capacity to collaborate across multidisciplinary teams distinguish top performers. These competencies are vital for designing effective analytics solutions, ensuring data integrity, and translating business needs into actionable data strategies.

What is a Data Analytics Architect job?

A Data Analytics Architect designs and implements data infrastructure, ensuring efficient data processing, storage, and analysis to support business intelligence and decision-making. They work with data engineers, analysts, and stakeholders to create scalable data solutions and optimize system performance. Their role involves selecting technologies, defining data models, and ensuring data security and governance.

What are the most commonly searched types of Data Analytics Architect jobs in Texas? The most popular types of Data Analytics Architect jobs in Texas are:
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What job categories do people searching Data Analytics Architect jobs in Texas look for? The top searched job categories for Data Analytics Architect jobs in Texas are:
What cities in Texas are hiring for Data Analytics Architect jobs? Cities in Texas with the most Data Analytics Architect job openings:
What are popular job titles related to Data Analytics Architect jobs in TX? For Data Analytics Architect jobs in TX, the most frequently searched job titles are:
Data Analytics Architect jobs near you
Infographic showing various Data Analytics Architect job openings in Texas as of July 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $166,533 per year, or $80.1 per hour.

Senior Data Analytics Architect

United IT Solutions

Southlake, TX • On-site

$63.25 - $84.75/hr

Other

Posted 25 days ago

Job description

Mandatory Skills  

·                  15+ years in Data Architecture, Data Analytics, Data governance, and Data Warehousing and architectural thought leadership 

·                  Proven experience with data strategy, roadmap, and end-to-end data landscape 

·                  Strong hands-on experience with Google Cloud Platform, especially Big Query 

·                  Expertise in Informatica IDMC  

·                  Advanced Complex SQL and Python skills  

·                  Experience designing enterprise data warehouse & analytics solutions  

·                  Ability to support and guide development and production systems  

·                  Strong business, communication, and stakeholder management skills 

·                  Google Cloud Platform Certification (Professional Data Engineer / Cloud Architect) 

Good to Have Skills  

·                  Experience with Google Cloud Platform Pub/Sub and Cloud Composer  

·                  Exposure to AI/ML ready data architectures  

·                  BQ Data Modeling and EDC 

·                  Cloud cost optimization experience 

·                  Consulting or large enterprise experience 

·                  Exposure to security and compliance frameworks in enterprise data platforms 

Role Overview

We are seeking an experienced Senior Data Analytics Architect with over 15 years of expertise in designing and delivering enterprise-scale data, analytics, and AI-enabled solutions. This role will lead the architecture, design, and implementation of modern data analytics platforms on Google Cloud Platform (Google Cloud Platform), enabling advanced analytics, data warehousing, and artificial intelligence use cases.

The Senior Data Analytics Architect will work closely with Product teams, development and production support teams, business users, and data consumers to ensure data solutions are scalable, reliable, secure, and aligned with business objectives.

Key ResponsibilitiesData & Analytics Architecture

·        Define and own the enterprise data and analytics architecture, aligning with business strategy and long-term analytics roadmap.

·        Architect end-to-end data warehousing, analytics, and AI-ready data platforms.

·        Design logical, physical, and analytical data models to support reporting, dashboards, advanced analytics, and AI/ML workloads.

·        Establish architecture standards, design patterns, and best practices for analytics and data platforms.

·        Architect data ingestion, streaming, and batch pipelines using Informatica IDMC, Pub/Sub, and Cloud Composer

 Solution Design & Implementation

·        Design and implement cloud-native analytics solutions on Google Cloud Platform, with a strong focus on Big Query.

·        Architect scalable data warehouses and analytics layers optimized for high-performance querying.

·        Design and oversee data ingestion, transformation, and orchestration pipelines using Informatica IDMC.

·        Enable analytics and AI use cases by ensuring data is well-structured, governed, and accessible.

Data Analytics & Artificial Intelligence Enablement

·        Support advanced analytics and AI initiatives by designing data architectures optimized for machine learning and data science workloads.

·        Collaborate with analytics and AI teams to ensure data availability, quality, and performance.

·        Ensure the data platform supports exploratory analytics, predictive modeling, and AI-driven insights.

 Development & Production Support

·        Provide hands-on architectural guidance to development teams throughout the development lifecycle.

·        Review SQL, Python code, and data pipelines for performance, scalability, and reliability.

·        Support production environments, including:

o   Monitoring and troubleshooting data pipeline failures.

o   Performance tuning and optimization

o   Root cause analysis and issue resolution

·        Ensure SLA adherence, data accuracy, and high availability of analytics systems.

 Stakeholder Collaboration

·        Partner with Product teams to translate product and analytics requirements into robust data solutions.

·        Work closely with business users and data consumers to understand reporting, analytics, and insight needs.

·        Communicate complex technical concepts clearly to both technical and non-technical stakeholders.

·       

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