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Data Structure Jobs in Texas (NOW HIRING)

Purple Drive

Data Modeler

Dallas, TX · On-site

$54.50 - $70.50/hr

Integrate structured and semi-structured data (e.g., JSON, XML) using Snowflakes native capabilities to support complex financial reporting. * Document data lineage and metadata to support ...

Ruri Software Technologies LLC

Data Engineer

Irving, TX · On-site

$109K - $132K/yr

Job Titile: Data Engineer Work Location; Irving, Texas Duration: 8+ Months Specific Skills ... Experience or knowledge of stream-processing systems: i.e., Storm, Spark-Structured-Streaming ...

E-Solutions

Data Modeler

Plano, TX · On-site

$52.50 - $68.25/hr

The ideal candidate will translate complex business requirements into effective and scalable data structures, ensuring data integrity, performance, and usability across systems. Responsibilities:

SourceDay, Inc.

Data Integration Engineer

Austin, TX · On-site

$113K - $136K/yr

Plans data integration process by developing common definitions of sourced data; designing common keys in physical data structure; establishing data integration specifications; examining data ...

SourceDay, Inc.

Data Integration Engineer

Austin, TX

$113K - $136K/yr

Plans data integration process by developing common definitions of sourced data; designing common keys in physical data structure; establishing data integration specifications; examining data ...

trane technologies

Data Manager

Tyler, TX · On-site

Work directly with the advanced analytics/visualization and decision science team members on data structure to support and enhance sophisticated Tableau dashboards and machine learning or AI models.

Trane Technologies plc

Data Manager

Tyler, TX · On-site

Work directly with the advanced analytics/visualization and decision science team members on data structure to support and enhance sophisticated Tableau dashboards and machine learning or AI models.

Triveni IT

Data Modeler

Irving, TX · On-site

$52.50 - $68.25/hr

As a Senior Data Modeler, you will be responsible for designing and modernizing the data structures for the solutions delivered across North America. You will create and maintain conceptual, logical ...

THOMSON REUTERS

Customer Data Analyst

Frisco, TX · Hybrid

Develop working knowledge of the CDP data structure - account and contact data, product entitlements, behavioral signals, and the Golden Record - to ensure audiences are accurate and fit for purpose.

CEDENT

Azure Data Engineer

Houston, TX

$109K - $131K/yr

Employ machine learning techniques to create and sustain data structures * Perform root cause analysis on external and internal processes and data to identify opportunity for improvement, resolve ...

Diverse Lynx

Data Modeler Architect

Carrollton, TX · On-site

$52.75 - $68.50/hr

... semi-structured data. • Strong understanding of dimensional modeling (Star Schema, Snowflake Schema). • Experience collaborating with cross-functional teams including Product Owners. • ...

Texans Credit Union

Data Engineer

Richardson, TX · On-site

$104K - $124K/yr

Design, develop, and maintain enterprise DataMarts that transform complex, disparate data sources into structured, business-ready datasets. * Apply advanced SQL expertise to build, optimize, and ...

Texans Credit Union

Data Engineer

Richardson, TX · On-site

$104K - $124K/yr

Design, develop, and maintain enterprise DataMarts that transform complex, disparate data sources into structured, business-ready datasets. * Apply advanced SQL expertise to build, optimize, and ...

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All JobsData Structure JobsData Structure Jobs in Texas

Data Structure information

See Texas salary details

$42.9K

$153.7K

$226.9K

How much do data structure jobs pay per year?

As of Jun 27, 2026, the average yearly pay for data structure in Texas is $153,740.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,400.00 and $158,400.00 per year, depending on experience, location, and employer.

What profession makes $400,000 a year?

In the field of data structures, senior software engineers, data architects, and machine learning engineers with extensive experience and advanced skills can earn salaries around $400,000 annually, especially in high-cost living areas or large tech companies. These roles typically require strong programming skills, knowledge of algorithms, and often advanced degrees or certifications. Compensation varies based on location, company size, and individual expertise.

What are data structures?

Data structures are specialized formats for organizing, processing, and storing data in computers so that it can be accessed and modified efficiently. Common types include arrays, linked lists, stacks, queues, trees, and graphs. Each data structure is designed to solve specific types of problems and optimize certain operations such as searching, sorting, or inserting data. Understanding data structures is fundamental for programming and software development, as they directly impact the performance and scalability of applications.

What is the difference between Data Structure vs Data Analyst?

AspectData StructureData Analyst
Required CredentialsComputer Science degree, programming skillsStatistics, data analysis certifications, degree in related fields
Work EnvironmentSoftware development, programming, algorithm designBusiness, finance, marketing, data interpretation
Industry UsageSoftware engineering, computer scienceBusiness intelligence, marketing, finance

Data Structures focus on organizing and storing data efficiently within software applications, requiring programming skills and technical knowledge. Data Analysts interpret data to provide insights, often using statistical tools and working closely with business teams. While Data Structures are foundational for software development, Data Analysts apply data to solve business problems. Both roles are essential in data-driven industries but serve different purposes and skill sets.

What is a Data Structure job?

A Data Structure job typically involves designing, implementing, and optimizing data storage and retrieval mechanisms in software applications. Professionals in this role work with different data structures like arrays, linked lists, trees, and graphs to improve the efficiency of algorithms. They are often employed in software development, data engineering, or system architecture roles, ensuring that data is managed efficiently for various applications. Strong problem-solving skills and proficiency in programming languages like Python, Java, or C++ are essential for success in this field.

What engineers make $500,000?

Senior software engineers, especially those working in high-demand areas like technology, finance, or specialized fields such as machine learning or cybersecurity, can earn $500,000 or more annually. Achieving this level typically requires extensive experience, advanced skills, and often stock options or bonuses in addition to base salary.

What jobs use data structures?

Data structures are fundamental in many jobs related to software development, such as software engineers, data analysts, and database administrators. These roles require understanding and implementing data structures like arrays, trees, and graphs to optimize algorithms and manage data efficiently.

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

To thrive as a Data Structures Engineer, you need a solid understanding of algorithms, programming languages (such as Java, C++, or Python), and a formal education in computer science or a related field. Familiarity with version control systems like Git, debugging tools, and experience with relevant libraries or frameworks are typically required. Strong analytical thinking, problem-solving abilities, and effective communication help you design efficient solutions and collaborate with other developers. These skills ensure robust, scalable software that meets performance requirements and supports business objectives.

What is a data structure job?

A data structure job involves designing, implementing, and maintaining data structures that organize and store data efficiently for software applications. These roles often require knowledge of algorithms, programming languages like Python or C++, and problem-solving skills to optimize data handling and performance.

What are some common challenges faced by professionals working with data structures in software development?

Professionals working with data structures often encounter challenges such as selecting the most efficient data structure for a specific application, optimizing memory usage, and ensuring code scalability as data volume grows. Collaboration with other team members, such as developers and data engineers, is essential to design robust solutions that balance performance and maintainability. Additionally, staying current with evolving algorithms and best practices helps address complex data manipulation tasks in real-world projects.
What are the most commonly searched types of Data Structure jobs in Texas? The most popular types of Data Structure jobs in Texas are:
What are popular job titles related to Data Structure jobs in Texas? For Data Structure jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Structure jobs in Texas look for? The top searched job categories for Data Structure jobs in Texas are:
Data Structure jobs near you
Infographic showing various Data Structure job openings in Texas as of June 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $153,740 per year, or $73.9 per hour.

Data Modeler

Purple Drive

Dallas, TX • On-site

$54.50 - $70.50/hr

Other

Posted 11 days ago

Job description

Overview:
Data Modeler
  • Design scalable data models optimized for Snowflakes cloud-native architecture, including use of virtual warehouses, clustering keys, and materialized views.
  • Develop conceptual, logical, and physical data models that align with financial regulatory requirements (e.g., Basel III, SOX, GDPR).
  • Collaborate with data engineers and architects to implement models that support real-time analytics, fraud detection, and risk management.
  • Ensure data quality and consistency across diverse financial systems such as trading platforms, customer onboarding, and compliance tools.
  • Integrate structured and semi-structured data (e.g., JSON, XML) using Snowflakes native capabilities to support complex financial reporting.
  • Document data lineage and metadata to support auditability and transparency for internal and external stakeholders.
  • Optimize data storage and query performance using Snowflake-specific features like automatic clustering and query profiling.
  • Support data governance initiatives by aligning models with enterprise data catalogs, stewardship policies, and access controls.
  • Collaborate with business analysts and compliance teams to translate financial reporting needs into robust data structures.
  • Continuously refine models based on evolving financial products, market conditions, and regulatory changes.

Qualifications Education Experience
  • Bachelors degree in Computer Science, Information Systems, Data Science, or a related field (Masters preferred).
  • 5 years of experience in data modeling, with at least 2 years working with Snowflake in a production environment.
  • Prior experience in the financial services industry, with familiarity in domains like risk, compliance, trading, or customer analytics.

Technical Skills
  • Proficiency in designing conceptual, logical, and physical data models.
  • Strong SQL skills and experience with Snowflake-specific features (e.g., Snowpipe, Streams, Tasks, Time Travel).
  • Familiarity with data modeling tools (e.g., ERStudio, ERwin, dbt, or similar).
  • Understanding of data warehousing principles, dimensional modeling, and normalization techniques.
  • Experience integrating structured and semi-structured data (e.g., JSON, XML) in Snowflake.
  • Domain Knowledge Knowledge of financial data structures and regulatory requirements (e.g., SOX, Basel III, GDPR).
  • Experience working with data governance, metadata management, and data quality frameworks.
  • Soft Skills Strong collaboration and communication skills to work with cross-functional teams including data engineers, analysts, and compliance officers.
  • Ability to translate business requirements into scalable and efficient data models.
  • Detail-oriented with a focus on data accuracy, consistency, and performance.

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