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Data Developer Jobs in Texas (NOW HIRING)

... Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss best design. • Gather inputs from multiple stakeholders to align ...

Data Modeler

Plano, TX · On-site

$52.25 - $68/hr

Have experience as a technical data developer and analyst with data architecture exposure. * Strong analytics and communication skills including ability to drive diverse group towards common goals ...

... Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss best design. • Gather inputs from multiple stakeholders to align ...

... Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss best design. • Gather inputs from multiple stakeholders to align ...

Data Strategy-Senior Manager

Dallas, TX · On-site

$124K - $280K/yr

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

Data Strategy-Senior Manager

Austin, TX · On-site

$124K - $280K/yr

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

Data Strategy-Senior Manager

Houston, TX · On-site

$124K - $280K/yr

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

Associate Data Engineer

Dallas, TX · On-site

$113.30K - $136K/yr

Exposure to Agile and DevOps practices. Required Skills: · Basic experience with Azure Data Factory or Azure Databricks. * SQL, Python. * PySpark * Familiarity with CI/CD tools (e.g., Azure DevOps, ...

Big Data

Plano, TX

$50.75 - $65.75/hr

Background in all aspects of software engineering with strong skills in parallel data processing, data flows, REST APIs, JSON, XML, and micro service architecture. * Must have strong programming ...

Sr. Data Engineer

Austin, TX · Hybrid

$113.50K - $136.30K/yr

Luna Data Solutions has an immediate long-term contract position opening (initial contract term ... Experience as a MuleSoft developer. * Experience developing using AI tools such as Snowflake Cortex ...

Data Engineer

Dallas, TX · On-site

$113.30K - $136K/yr

Role - Data Engineer • 2-3 years of hands-on experience in Data Engineering • Strong experience in Python and PySpark/Spark for large-scale data processing • Experience working with Databricks ...

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Data Developer information

See Texas salary details

$24

$49

$75

How much do data developer jobs pay per hour?

As of May 31, 2026, the average hourly pay for data developer in Texas is $49.49, according to ZipRecruiter salary data. Most workers in this role earn between $40.53 and $56.01 per hour, depending on experience, location, and employer.

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

To thrive as a Data Developer, you need strong programming skills (such as SQL, Python, or Java), a deep understanding of database design, and experience with data modeling, typically supported by a degree in computer science or a related field. Familiarity with tools like SQL Server, Oracle, ETL platforms, and cloud data services, as well as certifications in database technologies, are commonly required. Analytical thinking, problem-solving, and effective communication are crucial soft skills for collaborating with stakeholders and translating data needs into solutions. These competencies ensure efficient data management, support business intelligence efforts, and enable the delivery of reliable, scalable data systems.

How does a Data Developer typically collaborate with data analysts and data engineers within a project team?

Data Developers frequently work alongside data analysts and data engineers to design, build, and maintain robust data pipelines and databases. While data engineers often focus on the infrastructure and large-scale data architecture, Data Developers bridge the gap by implementing data models, optimizing queries, and ensuring data is accessible and reliable for analysis. Regular collaboration includes aligning on data requirements, troubleshooting data flow issues, and refining processes to support business intelligence and reporting needs. This teamwork ensures that data assets are accurate, up-to-date, and tailored for various stakeholder needs.

What are Data Developers?

Data Developers are professionals who design, build, and maintain systems that collect, store, process, and analyze large volumes of data. They work with databases, data pipelines, and various programming languages to ensure that an organization’s data is accessible, reliable, and efficiently managed. Data Developers often collaborate with data analysts, data scientists, and other IT staff to support business intelligence and data-driven decision-making. Their responsibilities may include writing complex SQL queries, developing ETL (extract, transform, load) processes, and optimizing database performance.

What is the difference between Data Developer vs Data Analyst?

AspectData DeveloperData Analyst
Primary RoleBuilds and maintains data pipelines, databases, and data infrastructureAnalyzes data to generate reports, insights, and support decision-making
Skills & CertificationsSQL, ETL tools, programming (Python, Java), database managementSQL, Excel, data visualization tools, statistical analysis
Work EnvironmentData engineering teams, IT departments, software development environmentsBusiness units, analytics teams, management
Industry UsageTechnology, finance, healthcare, any data-driven industryMarketing, finance, retail, business intelligence

While Data Developers focus on creating and maintaining the data infrastructure, Data Analysts interpret data to provide actionable insights. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

What are popular job titles related to Data Developer jobs in TX? For Data Developer jobs in TX, the most frequently searched job titles are:
Infographic showing various Data Developer job openings in Texas as of May 2026, with employment types broken down into 84% Full Time, 14% Part Time, 1% Temporary, and 1% Contract. Highlights an 49% Physical, 33% Hybrid, and 18% Remote job distribution, with an average salary of $102,937 per year, or $49.5 per hour.
AI Data Engineer - Manager

AI Data Engineer - Manager

Deloitte

Dallas, TX • On-site

Full-time

Posted 11 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th of 138 rated financial services


Job description

Job Summary:
Deloitte is a leading consulting firm focused on transforming the nature of work through innovative solutions. They are seeking an AI Data Engineer - Manager to lead data architecture and engineering delivery for AI/ML/GenAI solutions, ensuring data integrity and scalability while managing a team and collaborating with various stakeholders.
Responsibilities:
• Lead the data architecture and engineering delivery that enables AI/ML/GenAI solutions, ensuring data is trusted, secure, observable, and scalable from ingestion through consumption.
• Design and operationalize modern data and retrieval foundations to support LLM-powered applications (e.g., Claude, GPT/Codex, Gemini) including patterns such as RAG, embeddings, vector search, and governed access to structured and unstructured data.
• Manage day-to-day delivery with an onshore/offshore team, partnering with data science, ML engineering, and product stakeholders to translate use cases into production-ready pipelines and platforms with strong data governance, lineage, quality controls, and monitoring.
• Help define the AI/ML/GenAI technical direction and vision, ensuring alignment with strategic goals and digital transformation efforts.
• Translate the vision of business leaders into realistic technical implementations, while identifying misaligned initiatives and impractical use cases.
• Design end-to-end AI architectures, from data ingestion to model deployment, integrating with cloud and on-premises systems.
• Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
• Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage machine learning models and large language models.
• Conduct research to provide technical solutions to scale AI/ML powered features for real-world challenges, making trade-offs based on quality, scalability, performance, and cost.
• Lead the development of AI models (e.g., machine learning, natural language processing, computer vision) and implement scalable AI solutions.
• Collaborate with Enterprise, Application, Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss best design.
• Gather inputs from multiple stakeholders to align technical implementation with existing and future requirements.
• Serve as a technical advisor to leadership, providing insights on AI trends, potential business impacts, and implementation best practices.
• Be responsible for the successful execution of AI-powered applications using agile methodology.
• Audit AI tools and practices across data, models and software engineering, focusing on continuous improvement and feedback mechanisms.
• Contribute to standardizing CI/CD pipelines, user and service roles, and container creation, model consumption, testing, and deployment methodology based on business and security requirements.
• Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
• Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
• Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
• Break down client problems and bring an understanding of leading technology, analytics methods, tools, and operating model approaches.
• Build tools and capabilities that assist with data ingestion, feature engineering, data management, and organization.
• Design, implement, and maintain distributed computing solutions for data processing and model training, ensuring the security, scalability, and reliability of machine learning infrastructure.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Statistics, Data Science, Information Systems or related field.
• 6+ years of consulting experience leading delivery teams, including onshore and offshore team members
• 6+ years of experience gathering non-functional requirements and defining application architecture frameworks, including validation and testing deliverables
• 5+ years of experience working in an AI environment
• 5+ years of experience translating requirements into client ready design documents
• 5+ years of experience in software application architecture analysis, design, and delivery
• 5+ years of experience executing full system development life cycle implementations
• Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
• Limited immigration sponsorship may be available.
Preferred:
• Advanced degrees such as Masters or PhD are preferred
• Certifications in AI/ML technologies and Cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Azure AI Engineer, Azure Data Scientist, or Azure Solutions Architect
• 5 + years of experience in Data Science, Statistics, and Machine Learning
• 5+ years of experience in Generative AI/LLMs, preferably experienced in delivering and productionizing
• 5+ years of experience in machine learning model development, natural language processing, and data analysis; Experienced in Supervised and Unsupervised learning, feature engineering, model training, and deployment
• 5+ year of experience in implementing cloud-based AI/ML workloads on any of AWS, Microsoft and Azure.
Company:
Deloitte is a business consulting company that offers audit, consulting, financial advisory, and tax services. Founded in 1845, the company is headquartered in London, GBR, with a team of 10001+ employees. The company is currently Late Stage.

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