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Data Analytics Manager Jobs in Rosenberg, TX (NOW HIRING)

Experience with quality management systems (QMS) software or data management platforms preferred * Familiarity with Excel functions (pivot tables, charts, formulas) or similar analytics tools; basic ...

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 ... This role places a strong emphasis on data strategy, data management, and information-driven ...

*This is a contingent opportunity Data Analyst K2 Group is seeking a Data Analyst in support of Headquarters, Installation Management Command (IMCOM) Provost Marshal/Protection Support Services (PM ...

This role will manage big data that are cross-factory, cross-business-units and cross-systems. Responsibilities: * 10%, Analyze datasets using SQL, Cicada and Python. * 60%, Design, create, maintain ...

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Data Analytics Manager information

See Rosenberg, TX salary details

$27.7K

$86.7K

$153.5K

How much do data analytics manager jobs pay per year?

As of Jul 15, 2026, the average yearly pay for data analytics manager in Rosenberg, TX is $86,680.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,900.00 and $112,000.00 per year, depending on experience, location, and employer.

Will AI replace a data analyst?

AI tools can automate routine data processing and basic analysis tasks, but the role of a data analyst involves interpreting complex data, providing insights, and communicating findings, which require human judgment and domain expertise. Therefore, while AI may augment certain responsibilities, it is unlikely to fully replace data analysts in the near future, and skills in data storytelling and critical thinking remain essential.

How do Data Analytics Managers typically collaborate with stakeholders from non-technical departments?

Data Analytics Managers often act as a bridge between technical data teams and non-technical stakeholders, such as marketing, finance, or operations. They translate complex data insights into actionable recommendations and ensure that analyses align with business objectives. Regular communication, tailored presentations, and workshops are common practices to ensure all stakeholders understand the value and limitations of analytical findings. This collaborative approach helps drive data-driven decision-making across the organization.

What does a data analyst manager do?

A data analyst manager oversees a team of data analysts, guiding data collection, analysis, and reporting to support business decision-making. They develop strategies, ensure data accuracy, and often use tools like SQL, Excel, or data visualization software to interpret complex data sets. Strong leadership, communication skills, and knowledge of analytics tools are essential for this role.

How much do data analytics managers make?

Data analytics managers in the US typically earn a median salary of around $100,000 to $130,000 annually, with experienced professionals and those in high-demand industries earning higher. Salaries can vary based on location, education, certifications, and company size, and many roles require proficiency in tools like SQL, Python, or Tableau.

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

To thrive as a Data Analytics Manager, you need strong analytical skills, expertise in statistical methods, and a background in data science or a related field, often supported by a bachelor's or master's degree. Proficiency with data visualization tools (such as Tableau or Power BI), SQL, and analytics platforms like Python or R is typically required, along with experience in managing data projects. Leadership, strategic thinking, and effective communication are important soft skills for leading teams and translating data insights into actionable business strategies. These skills ensure that analytical initiatives drive business value and support informed decision-making across the organization.

What does a Data Analytics Manager do?

A Data Analytics Manager oversees data analysis operations and leads a team of analysts to extract actionable insights from data. They are responsible for managing data-driven projects, ensuring data integrity, and presenting findings to help guide business decisions. Their role often involves collaborating with various departments, setting analytic strategies, and ensuring that the team uses the most effective tools and methodologies. Additionally, they may handle hiring, training, and performance reviews of analytics staff.

What is the difference between Data Analytics Manager vs Data Analyst?

AspectData Analytics ManagerData Analyst
ResponsibilitiesOversees analytics projects, manages teams, develops strategiesPerforms data collection, cleaning, and analysis to generate reports
Required SkillsLeadership, project management, advanced analyticsData manipulation, statistical analysis, visualization
QualificationsBachelor's or Master's in Data Science, Analytics, or related fields; certifications like CAP or Microsoft Certified Data AnalystBachelor's in Statistics, Mathematics, or related fields; certifications like Microsoft Certified Data Analyst
Work EnvironmentCorporate offices, analytics teams, cross-department collaborationData teams, business units, often in office or remote settings

In summary, a Data Analytics Manager leads analytics teams and strategies, requiring leadership skills and advanced certifications, while a Data Analyst focuses on data processing and reporting, with more technical and analytical tasks. Both roles are essential in data-driven organizations and often work closely together.

Is a data analyst a high salary?

Data analysts typically earn moderate to high salaries depending on experience, industry, and location. While entry-level positions may have lower pay, experienced data analysts with skills in SQL, Excel, and data visualization tools can command higher salaries, especially in competitive markets.
What are the most commonly searched types of Data Analytics jobs in Rosenberg, TX? The most popular types of Data Analytics jobs in Rosenberg, TX are:
What job categories do people searching Data Analytics Manager jobs in Rosenberg, TX look for? The top searched job categories for Data Analytics Manager jobs in Rosenberg, TX are:
What cities near Rosenberg, TX are hiring for Data Analytics Manager jobs? Cities near Rosenberg, TX with the most Data Analytics Manager job openings:
Infographic showing various Data Analytics Manager job openings in Rosenberg, TX as of July 2026, with employment types broken down into 1% Internship, 87% Full Time, 7% Part Time, 1% Temporary, and 4% Contract. Highlights an 78% Physical, 5% Hybrid, and 17% Remote job distribution, with an average salary of $86,680 per year, or $41.7 per hour.
IT Data Analytics Director

Full-time

Posted 16 days ago


Job description

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