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Data Analytics Jobs in Houston, TX (NOW HIRING)

GHD

Data, Analytics & Insights - Executive Advisor

Houston, TX · Hybrid

$52.25 - $67.75/hr

We are seeking Data, Analytics & Insights - Executive Adviso r to shape, win and lead major client engagements, develop repeatable offers, and build high-performing teams aligned to client demand and ...

AaraTechnologies Inc

DATA ANALYST

Texas City, TX · On-site

Bachelor s degree in Data Analytics, Business, Healthcare Administration, or a related field (or equivalent experience) * Working knowledge of SQL * Experience with BI tools such as Tableau, Power BI ...

K2 Group Inc.

Data Analyst

Houston, TX · On-site

Bachelor's degree in data analytics, statistics, information systems, security studies, or related field. * Experience analyzing operational, security, or risk-related data in a DoW or federal ...

Foxconn Assembly LLC

Data Analyst

Houston, TX · On-site

Bachelor's degree in Data Analytics, Data Science, Information Systems or related fields. * Any Tableau or data visualization professional certifications are a plus.

bwp

Lead/Sr BSA Data & Analytics

Houston, TX

We are currently looking for a Lead/Sr BSA Data & Analytics for our Houston, TX office. POSITION DESCRIPTION: Serve as the key liaison between business stakeholders and the Data & Analytics team ...

Ketjen

Data Analytics and AI Leader

Houston, TX

Ketjen is hiring a senior leader to build its data, analytics, and AI capability. The final title and level will be set by Human Resources based on the candidate's background and scope.Today, Ketjen ...

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All JobsData Analytics JobsData Analytics Jobs in Houston, TX

Data Analytics information

See Houston, TX salary details

$23

$52

$90

How much do data analytics jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for data analytics in Houston, TX is $52.28, according to ZipRecruiter salary data. Most workers in this role earn between $42.02 and $59.23 per hour, depending on experience, location, and employer.

What kind of jobs can you get with data analytics?

Data analytics skills can lead to roles such as data analyst, business analyst, data scientist, and data engineer. These jobs involve analyzing data to support decision-making, creating reports, and developing data models using tools like SQL, Excel, and Python or R. Strong analytical skills and knowledge of data visualization are essential for these positions.

Is a data analyst still a good career?

Data analysts remain in high demand across industries due to the increasing reliance on data-driven decision making. Strong skills in tools like Excel, SQL, and visualization software, along with certifications, can enhance job prospects and career growth in this field.

How does a data analytics professional typically collaborate with other departments within an organization?

Data Analytics professionals frequently work alongside teams such as marketing, finance, operations, and product development to identify trends, solve business problems, and inform strategic decisions. Collaboration often involves gathering data requirements, interpreting findings, and presenting actionable insights in a clear and accessible manner. Effective communication and the ability to translate technical data into business terms are essential for ensuring recommendations are implemented and drive measurable impact. Regular cross-functional meetings and project-based teamwork are common, offering opportunities to learn from other disciplines and broaden one's organizational influence.

What jobs can a data analyst do?

A data analyst can work in roles such as business analyst, data specialist, or reporting analyst, focusing on collecting, processing, and analyzing data to support decision-making. They often use tools like Excel, SQL, and data visualization software, and may work in industries like finance, healthcare, marketing, or technology. Strong analytical skills and knowledge of statistical methods are essential for these positions.

What is the work for a data analytics?

A data analyst's work involves collecting, processing, and analyzing data to identify trends, support decision-making, and improve business outcomes. They use tools like Excel, SQL, and data visualization software, and often require strong analytical skills and attention to detail.

What is data analytics?

Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can inform decision-making. Professionals in this field use statistical techniques, programming, and data visualization tools to interpret complex data sets. Data analytics is applied in various industries, including business, healthcare, finance, and technology, to optimize operations, improve customer experiences, and drive strategic initiatives. The field often requires knowledge of tools like Excel, SQL, Python, and specialized analytics platforms.

What is the difference between Data Analytics vs Data Analyst?

AspectData AnalyticsData Analyst
Role FocusAnalyzing large datasets to identify trends and insightsInterpreting data, creating reports, and supporting decision-making
Skills & CertificationsStatistical skills, data visualization, tools like SQL, Python, RData visualization, Excel, SQL, basic statistical knowledge
Work EnvironmentOften in data teams, tech companies, or consulting firmsBusiness units, marketing, finance, or operations teams
Common UsageRefers to the field or disciplineRefers to the job role or position

While both roles involve working with data, Data Analytics typically refers to the broader field or discipline focused on analyzing data to extract insights. A Data Analyst is a specific job role within that field, responsible for interpreting data, creating reports, and supporting business decisions.

What are the key skills and qualifications needed to thrive as a data analytics professional, and why are they important?

To thrive as a Data Analytics professional, you need strong quantitative analysis skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Experience with technical tools like SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and sometimes certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate are highly valuable. Critical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills and qualities are crucial for transforming raw data into actionable insights that drive business decision-making.

What are the most commonly searched types of Data Analytics jobs in Houston, TX?

The most popular types of Data Analytics jobs in Houston, TX are:

What are popular job titles related to Data Analytics jobs in Houston, TX?

For Data Analytics jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Data Analytics jobs in Houston, TX look for?

The top searched job categories for Data Analytics jobs in Houston, TX are:

What cities near Houston, TX are hiring for Data Analytics jobs?

Cities near Houston, TX with the most Data Analytics job openings:

Data Analytics jobs near you
Infographic showing various Data Analytics job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $108,746 per year, or $52.3 per hour.

IT Data Analytics Director

Apache Corporation

Houston, TX • On-site

Full-time

Re-posted 15 days ago

Job description

Job Title: IT Data Analytics Director
Req Id: 12804
Specific Responsibilities
The Director of AI, Data Analytics, Data Engineering, Data Management, and Application Development, located in Houston, TX, is a senior leadership role responsible for overseeing and integrating multiple data-centric functions within the organization. This role ensures the strategic alignment of AI and data initiatives with business objectives, driving innovation, efficiency, and data-driven decision-making across the enterprise.
This role will be primarily responsible to:
  • Develop and execute the enterprise data, analytics, and AI strategy aligned with business objectives, digital transformation priorities, and long-term business value creation.
  • Lead, mentor, and develop multidisciplinary teams spanning data engineering, analytics, data management, AI/ML, digital products, and application delivery.
  • Foster a culture of innovation, collaboration, operational excellence, accountability, and continuous learning across the organization.
  • Partner with business and technology leaders to identify, prioritize, and deliver high-value data and AI initiatives that improve business performance and operational efficiency.
  • Establish and oversee enterprise analytics capabilities that provide actionable insights to support operational, commercial, and strategic decision-making.
  • Define and govern the enterprise data architecture, including cloud data platforms, data integration patterns, and scalable data products.
  • Oversee the design, implementation, and operation of secure, reliable, and scalable data pipelines, data services, and integration capabilities.
  • Develop and maintain policies, standards, and controls that protect the confidentiality, security, integrity, and availability of enterprise information assets.
  • Lead the identification, development, deployment, and governance of artificial intelligence and machine learning solutions that improve operational performance and business outcomes.
  • Establish responsible AI practices including AI governance, model lifecycle management, model risk management, transparency, explainability, and ongoing monitoring.
  • Drive adoption of generative AI capabilities and AI-assisted software development practices to improve productivity and accelerate solution delivery.
  • Evaluate emerging technologies, industry trends, and market developments to identify opportunities for innovation and competitive advantage.
  • Oversee the delivery, support, and lifecycle management of data-driven applications, low-code solutions, digital products, and workflow automation solutions that support business operations.
  • Ensure applications and digital solutions are scalable, secure, maintainable, user-friendly, and aligned with enterprise architecture standards.
  • Develop and manage annual operating plans, budgets, forecasts, and investment strategies within approved financial targets and organizational variance expectations.
  • Monitor technology spending, cloud and AI consumption, software licensing, and operational costs and implement cost optimization and FinOps practices across the portfolio.
  • Manage strategic relationships with technology vendors, service providers, system integrators, and implementation partners.
  • Lead technology evaluations, proof of concepts, contract negotiations, and vendor performance management activities.
  • Ensure alignment between enterprise IT, cloud, cybersecurity, operational technology (OT), and business organizations to support integrated digital capabilities across the enterprise.

Qualifications & Experience
The successful candidate will have the following qualifications and experience:
  • Bachelor's degree in computer science, data science, information technology, or a related field and/or a minimum of 10 years of experience in data analytics, data engineering, data management, data science, or application development.
  • 10 Years of experience in data analytics, data engineering, data management, data science, or application development.
  • At least 3 years of management experience.
  • Excellent leadership, people management, coaching, and team development capabilities.
  • Strong communication, presentation, negotiation, and stakeholder management skills, including interaction with executive leadership.
  • Strategic thinking with the ability to align technology investments and initiatives with business objectives and measurable business outcomes.
  • Strong analytical, critical thinking, and problem-solving capabilities.
  • Strong program, portfolio, project, and financial management skills.
  • Ability to collaborate effectively across business functions, technical organizations, and external partners.
  • Strong attention to detail and commitment to data quality, governance, and operational excellence.
  • Expertise in modern enterprise data architecture, data engineering, and cloud-native data platforms.
  • Experience designing, implementing, and managing scalable data pipelines, data platforms, and enterprise integration architectures.
  • Proficiency with business intelligence, reporting, and analytics platforms such as Power BI, Sigma, or similar technologies.
  • Experience with modern data platforms and technologies such as Snowflake, Databricks, or equivalent cloud-native solutions.
  • Experience with cloud computing platforms including AWS and Azure.
  • Strong understanding of enterprise data governance, metadata management, master data management, data quality, and information lifecycle management principles.
  • Knowledge of cybersecurity, data privacy, regulatory compliance, and information protection requirements applicable to enterprise data environments.
  • Experience implementing and governing artificial intelligence, machine learning, and generative AI solutions within enterprise environments including ChatGPT, Claude, and Copilot.
  • Knowledge of AI governance, model lifecycle management, model risk management, and responsible AI frameworks.
  • Familiarity with AI-assisted software development practices and modern software engineering methodologies.
  • Understanding of DevSecOps, DataOps, MLOps, CI/CD, and cloud operations practices.
  • Experience supporting low-code and workflow automation platforms.
  • Understanding of relational and analytical database technologies such as Oracle, Microsoft SQL Server, and cloud-native analytical databases.
  • Knowledge of cloud cost management, FinOps practices, and technology portfolio optimization.
  • Experience managing technology vendors, software suppliers, system integrators, and strategic technology partnerships.
  • Ability to evaluate emerging technologies and determine business applicability and value.
  • Understanding of operational technology (OT), industrial data management, and enterprise integration challenges in complex industrial environments.
  • Experience in upstream environments is preferred.
  • Demonstrated ability to balance innovation, operational reliability, cybersecurity, and regulatory compliance in large enterprise environments.

Competencies
The successful candidate will lead by example through successfully demonstrating the following:
  • Core Competencies
    • Communication: Writes, speaks, and presents information effectively and persuasively across communication setting;
    • Results: Pursues work with energy, drive, and results orientation to positively impact Apache's business success;
    • Collaboration: Works in partnership with others and encourages different perspectives, while building and maintaining trust; and
    • Culture: Willingness and ability to align one's behavior with the needs, priorities, and goals of Apache.
  • Leadership Competencies
    • Servant Leadership: Inspires and enables performance excellence through feedback, empathy, development and empowerment;
    • Strategic Mindset: Applies business acumen to see the big picture, understand business issues, and exhibit financial stewardship;
    • Change Leadership: Inspires change by challenging the status quo, generating support, and executing improvement projects to achieve business outcomes; and
    • Leading Effective Teams: Enables performance excellence through effective structure, delegation, and motivation.

Company Overview
Our primary product is energy, and where there is affordable, abundant energy, people are healthier, have access to better education, and are given greater opportunities to elevate their families to higher standards of living.
Nearly 3 billion people - roughly one-third of the global population - live without electricity or without clean cooking facilities. We are committed to providing energy in innovative and more sustainable ways to help raise the standard of living for those living in energy poverty and to meet the ongoing demands of people and economies around the world.
The products we deliver power increasingly cleaner electricity across the globe, fuel tractors and trucks, make fertilizer to keep the world's food supply on the table, and heat our schools, hospitals and businesses.
Our employees bring a wide range of talents and skills to the job every day to tackle complex business challenges. We believe in providing a truly rewarding work environment supported by a benefits platform that ranks among the best in our peer group. Our company offers career development opportunities where employees can grow personally and professionally. We promote employee benefits that cultivate a family-friendly work environment and focus on our employees' overall well-being.
We are committed to being a workplace where all employees are valued and can thrive with a sense of belonging. Our commitment to non-discriminatory, equal employment opportunities benefits our individual employees, our company and our external stakeholders; we are better as an organization when various experiences, ideas, and perspectives are brought to the table.
Apache Corporation is a wholly owned subsidiary of APA Corporation (NASDAQ:APA). Apache has operations in the United States, Egypt's Western Desert and the United Kingdom's North Sea and a sister company with exploration opportunities offshore Suriname. Whether supporting Apache, APA Corporation or one of its subsidiaries, team members are employed by Apache Corporation.
For additional information about APA Corporation, please visit:
Portfolio
Sustainability
Investors
www.apacorp.com
Apache Statement on Hiring
To provide genuine equal opportunity to all people, it is the policy of Apache Corporation and its subsidiaries to base all employment-related decisions and actions exclusively on employment-related criteria. To provide genuine equal opportunity to all people, it is the policy of Apache Corporation and its subsidiaries to provide broad dissemination of job opportunities, as consistent with the nature of the positions. To provide genuine equal opportunity to all people, it is the policy of Apache Corporation and its subsidiaries to review its employment-related policies and actions on a regular basis to ensure that their application is consistent with their intent.
Equal Employment Opportunity

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