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Technical Data Jobs in Texas (NOW HIRING)

Technical background on implementation of APIs to merge data between different systems * Experience with or knowledge of surface facilities, emissions estimation, and power systems preferred * Strong ...

Technical Data Project Manager Location: Dallas, TX (onsite day 1) Only Locals preferred. Contract JD : * Banking industry experience * Data program experience * Played technical role earlier in the ...

Senior Technical Data Center Manager

Amarillo, TX · On-site

$103K - $143K/yr

Description Role Overview Fermi America is seeking a Senior Data Center Technical Manager to serve as the technical authority for all data center engineering and infrastructure systems across Fermi ...

Senior Technical Data Center Manager

Amarillo, TX · On-site

$103K - $143K/yr

Role Overview Fermi America is seeking a Senior Data Center Technical Manager to serve as the technical authority for all data center engineering and infrastructure systems across Fermi's hyperscale ...

The GIST We're hoping you'll augment our team by bringing your data and technology expertise to ... to technical and nontechnical audiences at various hierarchical levels. * Working knowledge of ...

The GIST We're hoping you'll augment our team by bringing your data and technology expertise to ... to technical and nontechnical audiences at various hierarchical levels. * Working knowledge of ...

Global Data Center Technical Leader Collaborate with Innovative 3Mers Around the World Choosing where to start and grow your career has a major impact on your professional and personal life, so it ...

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Technical Data information

Is 40 too late for data science?

Age is not a strict barrier for a career in data science, and many professionals transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, along with practical experience through projects or certifications. Continuous learning and adapting to new technologies are key regardless of age.

What is the highest paying job in data?

The highest paying roles in data typically include Data Science Directors, Chief Data Officers, and Data Engineering Managers, with salaries often exceeding $150,000 annually. These positions require advanced skills in data analysis, machine learning, and leadership, and often demand extensive experience and relevant certifications.

What jobs pay 500,000 a year in the US?

In the field of technical data, high-paying roles such as senior data scientists, data engineering managers, and chief data officers can earn $500,000 or more annually, especially with extensive experience, advanced skills in machine learning and big data tools, and leadership responsibilities. These positions often require advanced degrees, certifications, and a strong track record in data management and analytics.

What does a data technician do?

A data technician is responsible for collecting, organizing, and maintaining data to ensure accuracy and accessibility. They often use tools like databases and spreadsheets, perform data entry, and support data analysis tasks in various industries. Attention to detail and knowledge of data management software are essential skills for this role.
What cities in Texas are hiring for Technical Data jobs? Cities in Texas with the most Technical Data job openings:
Infographic showing various Technical Data job openings in Texas as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Technical Data Steward

NTT DATA North America

Dallas, TX • On-site

Full-time

Posted 7 days ago


Job description

Job Summary:
NTT DATA North America is a trusted global innovator of business and technology services. They are seeking a Technical Data Steward responsible for maintaining technical metadata, supporting data governance policies, and ensuring data quality across various domains.
Responsibilities:
• Maintain and update technical metadata in the enterprise data catalog.
• Document and maintain data lineage, data flows, schemas, and system integrations.
• Support implementation of data governance policies, standards, and controls.
• Collaborate with data engineering and product teams on data models, pipelines, and schema changes.
• Manage technical change requests and assess downstream impacts.
• Support configuration and use of data governance tools (catalog, lineage, metadata platforms).
• Identify opportunities to improve metadata automation and governance processes.
• Monitor data quality rules, dashboards, and automated checks for assigned domains.
• Identify, investigate, and document data quality issues; coordinate remediation with engineering and business teams.
• Perform root‐cause analysis and recommend long‐term corrective actions.
• Ensure data quality dimensions (accuracy, completeness, timeliness, consistency) are met.
• Track and report data quality trends, recurring issues, and improvement progress.
• Support creation and maintenance of data quality rules, thresholds, and validation logic.
Qualifications:
Required:
• Maintain and update technical metadata in the enterprise data catalog.
• Document and maintain data lineage, data flows, schemas, and system integrations.
• Support implementation of data governance policies, standards, and controls.
• Collaborate with data engineering and product teams on data models, pipelines, and schema changes.
• Manage technical change requests and assess downstream impacts.
• Support configuration and use of data governance tools (catalog, lineage, metadata platforms).
• Identify opportunities to improve metadata automation and governance processes.
• Monitor data quality rules, dashboards, and automated checks for assigned domains.
• Identify, investigate, and document data quality issues; coordinate remediation with engineering and business teams.
• Perform root‐cause analysis and recommend long‐term corrective actions.
• Ensure data quality dimensions (accuracy, completeness, timeliness, consistency) are met.
• Track and report data quality trends, recurring issues, and improvement progress.
• Support creation and maintenance of data quality rules, thresholds, and validation logic.
Company:
NTT DATA, Inc. is a trusted global innovator of business and technology services. Founded in 1988, the company is headquartered in Plano, USA, with a team of 10001+ employees. The company is currently Late Stage.