Data Operations Manager Jobs in Texas
Data Operations Manager jobs in Texas are in strong demand, with active hiring concentrated in enterprise technology, financial services, healthcare systems, and energy sectors, from early-career analysts stepping into management through seasoned senior directors. Dallas-Fort Worth, Houston, and Austin anchor the market, where employers like Dell Technologies, JPMorgan Chase, and MD Anderson Cancer Center have long maintained large data operations teams. The most sought-after specialties in Texas right now are data pipeline management, operational analytics, and data governance. Find a role that fits below and apply directly.
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Showing 4 of 99+ Data Operations Manager jobs
THE PERSON:
KEY RESPONSIBILITIES:
- Predictive Modeling & Machine Learning:
- Develop and deploy predictive models using machine learning algorithms (e.g., XGBoost, Random Forest) to address business challenges such as customer segmentation and revenue forecast.
- Build end-to-end ML pipelines from data ingestion to model deployment, ensuring scalability and reliability.
- Time-Series Forecasting:
- Create robust time-series forecasting models for revenue, demand, and operational metrics using techniques like ARIMA, Prophet, Bayesian methods, and hybrid approaches.
- Partner with finance, sales, and operations teams to integrate forecasts into strategic planning and decision-making processes.
- Generative AI & Advanced Analytics:
- Design and implement generative AI solutions (e.g., LLMs, GANs) for business applications such as information retrieval, workflow automation, and AI-driven decision systems.
Data Pipeline & Infrastructure:
- Collaborate with data engineering teams to design and maintain scalable data pipelines using tools like Airflow, KNIME, or custom shell scripting.
- Leverage big data frameworks (e.g., Snowflake, Hadoop, Spark) for efficient data processing and storage.
- Exploratory Data Analysis & Visualization:
- Perform exploratory data analysis to uncover patterns and insights from structured and unstructured data sources.
- Develop visualizations using tools such as Plotly, Matplotlib and Seaborn to communicate findings effectively to stakeholders.
- Collaboration & Impact Measurement:
- Work closely with business leaders, data engineers, and BI teams to align on business needs and deliver impactful solutions.
- Monitor model performance post-deployment and iterate on models to ensure continued business impact.
- Continuous Learning & Innovation:
- Stay updated on emerging technologies in AI, machine learning, and generative models.
- Experiment with new tools and techniques to enhance team capabilities and drive innovation.
QUALIFICATIONS:
-
Education:
Bachelor’s degree (Master’s preferred) in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field. - Technical Skills:
- Proficiency in Python, SQL, and other programming languages.
- Strong understanding of machine learning algorithms and statistical techniques.
- Hands-on experience with ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and frameworks for generative AI.
- Familiarity with time-series forecasting methods and tools.
- Experience working with big data technologies (e.g., Snowflake, Hadoop, Spark).
- Basic knowledge of UNIX shell scripting (Bash, Zsh).
- Experience:
- Minimum of 3+ years of experience in data science or related fields.
- Demonstrated ability to deliver end-to-end ML projects from start to finish.
- Experience with version control tools like Git and GitHub.
- Business Acumen:
- Ability to translate technical insights into actionable business strategies.
- Strong communication skills to effectively collaborate with cross-functional teams.
#LI-RF1
AMD does not accept unsolicited resumes from headhunters, recruitment agencies or fee based recruitment services. AMD and its subsidiaries are equal opportunity employers and will consider all applicants without regard to race, marital status, sex, age, color, religion, national origin, veteran status, disability or any other characteristic protected by law. EOE/MFDV
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
THE PERSON:
KEY RESPONSIBILITIES:
- Predictive Modeling & Machine Learning:
- Develop and deploy predictive models using machine learning algorithms (e.g., XGBoost, Random Forest) to address business challenges such as customer segmentation and revenue forecast.
- Build end-to-end ML pipelines from data ingestion to model deployment, ensuring scalability and reliability.
- Time-Series Forecasting:
- Create robust time-series forecasting models for revenue, demand, and operational metrics using techniques like ARIMA, Prophet, Bayesian methods, and hybrid approaches.
- Partner with finance, sales, and operations teams to integrate forecasts into strategic planning and decision-making processes.
- Generative AI & Advanced Analytics:
- Design and implement generative AI solutions (e.g., LLMs, GANs) for business applications such as information retrieval, workflow automation, and AI-driven decision systems.
Data Pipeline & Infrastructure:
- Collaborate with data engineering teams to design and maintain scalable data pipelines using tools like Airflow, KNIME, or custom shell scripting.
- Leverage big data frameworks (e.g., Snowflake, Hadoop, Spark) for efficient data processing and storage.
- Exploratory Data Analysis & Visualization:
- Perform exploratory data analysis to uncover patterns and insights from structured and unstructured data sources.
- Develop visualizations using tools such as Plotly, Matplotlib and Seaborn to communicate findings effectively to stakeholders.
- Collaboration & Impact Measurement:
- Work closely with business leaders, data engineers, and BI teams to align on business needs and deliver impactful solutions.
- Monitor model performance post-deployment and iterate on models to ensure continued business impact.
- Continuous Learning & Innovation:
- Stay updated on emerging technologies in AI, machine learning, and generative models.
- Experiment with new tools and techniques to enhance team capabilities and drive innovation.
QUALIFICATIONS:
-
Education:
Bachelor’s degree (Master’s preferred) in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field. - Technical Skills:
- Proficiency in Python, SQL, and other programming languages.
- Strong understanding of machine learning algorithms and statistical techniques.
- Hands-on experience with ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and frameworks for generative AI.
- Familiarity with time-series forecasting methods and tools.
- Experience working with big data technologies (e.g., Snowflake, Hadoop, Spark).
- Basic knowledge of UNIX shell scripting (Bash, Zsh).
- Experience:
- Minimum of 3+ years of experience in data science or related fields.
- Demonstrated ability to deliver end-to-end ML projects from start to finish.
- Experience with version control tools like Git and GitHub.
- Business Acumen:
- Ability to translate technical insights into actionable business strategies.
- Strong communication skills to effectively collaborate with cross-functional teams.
#LI-RF1
AMD does not accept unsolicited resumes from headhunters, recruitment agencies or fee based recruitment services. AMD and its subsidiaries are equal opportunity employers and will consider all applicants without regard to race, marital status, sex, age, color, religion, national origin, veteran status, disability or any other characteristic protected by law. EOE/MFDV
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
See All 99 Data Operations Manager Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
Find Data Operations Manager JobsData Operations Manager Jobs by City in Texas
Where Texas roles are concentrated, by current openings.
Data Operations Manager Job Market in Texas
A snapshot from current Texas openings, updated as new roles post.
Who's Hiring
- Google15
- Amazon6
- Meta3
- Apple3
- Digital Realty3
Top Industries Hiring
- Insurance
- Technology & Software
- Electronics & Hardware
- Construction & Real Estate
- Consulting & Professional Services
What Texas Employers Look For
The qualifications that appear most often in data operations manager jobs across Texas.
- Bachelor's degree in information systems, computer science, business analytics, or a related field
- Proven experience managing data pipelines, ETL processes, and database operations at scale
- Proficiency with SQL and at least one major cloud platform such as AWS, Azure, or Google Cloud
- Experience leading cross-functional data teams and coordinating with engineering and analytics stakeholders
- Familiarity with data governance frameworks, data quality standards, and compliance requirements
- Strong communication skills to translate technical data issues into business-facing recommendations
Data Operations Manager Jobs in Texas: Frequently Asked Questions
How do you become a data operations manager in Texas?
The typical path starts with a bachelor's degree in information systems, computer science, or business analytics, followed by several years in data analyst, data engineer, or database administrator roles. Texas does not require a state-issued license for this position. Most hiring managers in Texas look for hands-on experience with cloud platforms and ETL tools, and certifications from AWS, Microsoft Azure, or Google Cloud can meaningfully strengthen a candidacy before moving into a management track.
How much do data operations managers make in Texas?
Data operations managers in Texas earn a median of about $171,530 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $106,390 for the lowest 10% to over $277,160 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire data operations managers in Texas?
Employers hiring data operations managers in Texas right now include Google, Amazon, and Meta, based on current listings on Migrate Mate as of August 2026. Texas's concentration of Fortune 500 headquarters, major hospital networks, and energy companies means demand for this role is spread across several distinct industries rather than clustering in a single sector.
Which Texas cities have the most data operations manager jobs?
Austin, Dallas, and Houston account for the largest share of data operations manager openings in Texas. Dallas-Fort Worth's density of corporate headquarters in finance and technology drives the bulk of listings, while Houston's energy and healthcare sectors generate consistent demand, and Austin's fast-growing tech industry has added a significant number of roles over the past several years.
Are there remote data operations manager jobs in Texas?
Yes, and more than most fields. About 36% of data operations manager openings tied to Texas are remote or hybrid as of August 2026, reflecting how much of the work centers on managing cloud-based systems and collaborating through digital tools rather than being on-site. The parts of the role most commonly done remotely include pipeline monitoring, reporting, vendor coordination, and team oversight.
How can I get hired as a data operations manager in Texas with little or no experience?
The most realistic entry point is landing a data analyst or junior data engineer role first, then building toward management. Large Texas employers such as Texas Health Resources, AT&T, and ExxonMobil run rotational analytics programs and internal development tracks that move strong individual contributors into operations leadership. Building a portfolio of SQL projects and earning a cloud platform certification from AWS or Microsoft sharpens a candidacy considerably before applying for manager-level openings.
Where can I find and apply to data operations manager jobs in Texas?
You can find and apply to data operations manager jobs in Texas on Migrate Mate, which lists current Texas openings across industries and metro areas. Find roles that fit your experience and location and apply directly through each listing.
See All 99 Data Operations Manager Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
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