ZipRecruiter

Log In

1

Data Ops Engineer Jobs in Texas (NOW HIRING)

Vkore Solutions

GenAI Engineer-W2

Austin, TX · On-site

We are looking for a GenAI Ops Engineer to train, fine-tune, and deploy Generative AI models (LLMs ... Manage datasets, preprocess data, and implement RAG with vector databases (FAISS, Chroma, Pinecone)

Oxy

Advisor IT Systems - AI/ML Ops

Houston, TX · On-site

This role bridges data science, cloud engineering, and operations to ensure reliable, scalable, and ... Ops. * Good grasp of software architecture principles and systems design * Strong proficiency in ...

Oxy

Advisor IT Systems - AI/ML Ops

Houston, TX · On-site

This role bridges data science, cloud engineering, and operations to ensure reliable, scalable, and ... Ops. * Good grasp of software architecture principles and systems design * Strong proficiency in ...

Cliftonlarsonallen

Lead ML Ops Engineer

Fort Worth, TX

$98K - $129K/yr

Degree in computer science, data science, or related field preferred. Technical Competencies ... Leadershiplevel expertise in AI/ML platform engineering, spanning MLOps, LLMOps, and AIOps.

The Friedkin Group

Dev/Sec Ops Engineer

Houston, TX · On-site

$48.75 - $67/hr

A Day in The Life We're seeking a DevSecOps Engineer to own the secure delivery pipeline and ... Knowledge of data protection (PII), tokenization, and regional compliance. * Background in ...

The Friedkin Group

Dev/Sec Ops Engineer

Houston, TX

$48.75 - $67/hr

A Day in The Life We're seeking a DevSecOps Engineer to own the secure delivery pipeline and ... Knowledge of data protection (PII), tokenization, and regional compliance. * Background in ...

Cliftonlarsonallen

Lead ML Ops Engineer

Austin, TX · On-site

$101K - $133K/yr

Degree in computer science, data science, or related field preferred. Technical Competencies ... Leadershiplevel expertise in AI/ML platform engineering, spanning MLOps, LLMOps, and AIOps.

CliftonLarsonAllen

Lead ML Ops engineer

Fort Worth, TX

$98K - $129K/yr

Degree in computer science, data science, or related field preferred. Technical Competencies ... Leadershiplevel expertise in AI/ML platform engineering, spanning MLOps, LLMOps, and AIOps.

CliftonLarsonAllen

Lead ML Ops engineer

Austin, TX

$101K - $133K/yr

Degree in computer science, data science, or related field preferred. Technical Competencies ... Leadershiplevel expertise in AI/ML platform engineering, spanning MLOps, LLMOps, and AIOps.

Service Experts

Principal Architect

Richardson, TX · Hybrid

... engineering, analytics, and platform operations teams. Act as the single architectural and ... Data Operations & Reliability Own the Data Ops operating model including incident management ...

next page

Showing results 1-20

All JobsData Ops Engineer JobsData Ops Engineer Jobs in Texas

Data Ops Engineer information

See Texas salary details

$41.5K

$120.9K

$165.4K

How much do data ops engineer jobs pay per year?

As of Jun 12, 2026, the average yearly pay for data ops engineer in Texas is $120,851.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,700.00 and $128,100.00 per year, depending on experience, location, and employer.

What engineers make $300,000 a year?

Senior Data Ops Engineers with extensive experience, advanced skills in cloud platforms, automation, and data pipeline management can earn $300,000 or more annually. High compensation is often associated with roles in large organizations, specialized expertise, and leadership responsibilities.

Is DataOps a good career?

DataOps engineers focus on streamlining data workflows, automation, and integration using tools like SQL, Python, and cloud platforms. The role is in demand due to the growth of data-driven decision-making and offers opportunities for advancement in analytics, data engineering, and DevOps environments.

What are Data Ops Engineers?

Data Ops Engineers are professionals who bridge the gap between data engineering and operations. They focus on automating, monitoring, and optimizing data pipelines to ensure reliable, efficient, and secure data flow within organizations. Their responsibilities often include managing data integration, workflow orchestration, deployment of data infrastructure, and implementing best practices for data quality and governance. Data Ops Engineers work closely with data scientists, analysts, and IT teams to support data-driven decision-making and maintain high data availability. Their role is crucial in modern organizations that rely on large-scale data processing and analytics.

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

To thrive as a Data Ops Engineer, you need a solid background in data engineering, automation, and cloud infrastructure, often supported by a degree in computer science or related field. Experience with tools like Apache Airflow, Docker, Kubernetes, CI/CD pipelines, and proficiency in scripting languages such as Python or Bash is typically required. Strong problem-solving skills, attention to detail, and effective communication help you collaborate with data teams and troubleshoot complex data workflows. These skills ensure reliable data delivery, streamlined operations, and scalable solutions that support organizational data goals.

What does a DataOps engineer do?

A DataOps engineer is responsible for managing and automating data pipelines, ensuring data quality, and optimizing data workflows for faster and reliable data delivery. They often use tools like Apache Airflow, Jenkins, or Kubernetes and collaborate with data engineers and analysts to improve data processes and infrastructure.

What is the difference between Data Ops Engineer vs Data Engineer?

AspectData Ops EngineerData Engineer
CredentialsCertifications in data management, cloud platforms, scriptingCertifications in data engineering, SQL, cloud services
Work EnvironmentFocus on data pipelines, automation, deployment, and monitoringFocus on data modeling, ETL processes, database design
Industry UsageUsed in organizations emphasizing data operations, automation, and DevOps practicesUsed in data-centric roles focusing on building data infrastructure

While both roles work with data infrastructure, Data Ops Engineers primarily focus on automating and managing data pipelines and deployment processes, whereas Data Engineers concentrate on designing and building data systems. The roles often overlap but differ in their core focus areas and responsibilities.

How does a Data Ops Engineer typically collaborate with data scientists and software engineers within an organization?

Data Ops Engineers play a crucial role in bridging the gap between data science and engineering teams. They ensure smooth data pipeline operations, help automate workflows, and support data scientists by providing reliable, scalable infrastructure. Collaboration often involves participating in cross-functional meetings to understand data requirements, troubleshooting data quality issues, and implementing solutions that enable efficient experimentation and model deployment. This collaborative environment helps facilitate quick iterations and reliable delivery of data products.

What engineers make $500,000?

Senior data engineers, especially those with expertise in cloud platforms, big data tools, and advanced analytics, can earn $500,000 or more annually in high-demand industries. Achieving this level typically requires extensive experience, specialized skills, and often leadership responsibilities or equity compensation.
What are popular job titles related to Data Ops Engineer jobs in Texas? For Data Ops Engineer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Ops Engineer jobs in Texas look for? The top searched job categories for Data Ops Engineer jobs in Texas are:
Data Ops Engineer jobs near you
Infographic showing various Data Ops Engineer job openings in Texas as of June 2026, with employment types broken down into 2% As Needed, 62% Full Time, 35% Part Time, and 1% Temporary. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $120,851 per year, or $58.1 per hour.

AI Marketing Ops/Engineer Consultant

Right Side Up

Austin, TX • On-site, Remote

Full-time

Posted 29 days ago

Job description

About Right Side Up
Please note, this posting is to highlight joining Right Side Up's talent collective specifically and is not representing an internal full-time role, or a current opportunity with a client.
Right Side Up is a collective of premium marketing talent-with all of the marketing chops, and none of the agency fluff. We're trusted by the most respected early-stage ventures, the fastest-growing tech companies, and well-established Fortune 500 teams to do one thing better: Growth. We have over 250+ clients including Stitch Fix, Sephora, Yelp, Sun Basket, Crunchbase, DoorDash, Calm, and more.
About the Role
The AI Marketing Ops Consultant sits at the intersection of marketing and technology. You're the person who doesn't just identify where AI can help - you build it. You translate marketing workflows into working automations, connect the tools, write the prompts, and ship the thing.
You'll be embedded with marketing teams who want to move faster and smarter, and you'll help them do exactly that: less manual work, better signals, more leverage from the tech stack they already have.
What You'll Do
  • Build and deploy AI-powered marketing workflows - think content generation pipelines, lead enrichment automations, personalization logic, and reporting systems that actually run themselves
  • Audit existing marketing ops setups and identify where AI can cut friction or unlock scale
  • Integrate LLM APIs, no-code/low-code tools, and marketing platforms (CRM, MAP, CMS, ad platforms) into cohesive workflows
  • Write and iterate on prompts, system instructions, and structured outputs tailored to specific marketing use cases
  • Document what you build so teams can maintain and extend it without you
  • Collaborate with strategists, growth marketers, and data teams to scope, pressure-test, and ship solutions
  • Track what's working - measuring time saved, output quality, and downstream marketing impact

What We're Looking For
  • 3-5+ years of experience in marketing operations, growth engineering, or a similar role at a tech company or agency
  • Hands-on experience building with AI tools - LLM APIs (OpenAI, Anthropic, etc.), agents, or AI-native platforms
  • Strong command of the marketing tech stack: CRM, MAP, data pipelines, and ad platforms
  • Comfortable writing code or using low-code tools (Python, JavaScript, Zapier, Make, n8n, etc.) to connect systems and automate workflows
  • Sharp instincts for marketing - you understand the goals behind the work, not just the mechanics
  • Clear communicator who can explain what you built and why it matters to a non-technical stakeholder
  • Self-directed and delivery-oriented; you're energized by shipping, not just scoping

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Apply