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Analytics Engineer Jobs in Houston, TX (NOW HIRING)

Axiomspace

Lead Thermal Analysis Engineer

Houston, TX · On-site

SUMMARY The Lead Thermal Analysis Engineer is responsible for developing and analyzing thermal models of spacecraft components and systems using tools like SINDA/FLUINT and Thermal Desktop. This role ...

Garver

Traffic Analysis Engineer

Houston, TX · On-site

$83K - $113K/yr

Garver is seeking a highly-motivated Traffic Analysis Engineer in our Houston, TX office to add to our growing traffic and transportation planning team. The ideal candidate would have 5-10 years of ...

Garver

Traffic Analysis Engineer

Houston, TX · On-site

$83K - $113K/yr

Garver is seeking a highly-motivated Traffic Analysis Engineer in our Houston, TX office to add to our growing traffic and transportation planning team. The ideal candidate would have 5-10 years of ...

Microvast

BMS Data Analysis Engineer

Houston, TX · On-site

$109K - $131K/yr

They are seeking a highly skilled BMS Data Analysis Engineer to join their team, responsible for designing, developing, and optimizing advanced algorithms to solve complex problems in battery systems.

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All JobsAnalytics Engineer JobsAnalytics Engineer Jobs in Houston, TX

Analytics Engineer information

See Houston, TX salary details

$60.6K

$105.8K

$172.5K

How much do analytics engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for analytics engineer in Houston, TX is $105,775.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,990.00 and $118,728.00 per year, depending on experience, location, and employer.

What do analytics engineers do?

Analytics engineers design, build, and maintain data pipelines and infrastructure to enable data analysis and reporting. They work with tools like SQL, Python, and data warehouses to ensure data is accurate, accessible, and well-structured for analysts and data scientists. Their role often involves collaborating with teams to optimize data workflows and ensure data quality.

What are the key skills and qualifications needed to thrive as an analytics engineer, and why are they important?

To thrive as an Analytics Engineer, you need a strong foundation in data modeling, SQL, and analytics engineering principles, often supported by a degree in computer science, data science, or a related field. Proficiency with data transformation tools such as dbt, cloud data warehouses like Snowflake or BigQuery, and version control systems like Git is essential. Strong problem-solving skills, communication, and collaboration abilities help translate business needs into scalable data solutions and foster teamwork. These skills and qualities are crucial for ensuring data quality, building reliable analytics infrastructure, and enabling data-driven decision-making across organizations.

What is the difference between Analytics Engineer vs Data Engineer?

AspectAnalytics EngineerData Engineer
CredentialsOften requires SQL, Python, data modeling certificationsRequires similar skills, often with additional focus on infrastructure and systems
Work EnvironmentFocuses on data analysis, visualization, and reportingBuilds data pipelines, manages data infrastructure
Industry UsageCommon in analytics teams, BI, and data-driven rolesPrevalent in data engineering, data platform teams

While both roles work closely with data, Analytics Engineers primarily focus on transforming data for analysis and visualization, whereas Data Engineers build the infrastructure and pipelines that enable data access. Understanding these differences helps in choosing the right career path or job role.

How does an analytics engineer typically collaborate with data scientists and business stakeholders on projects?

Analytics Engineers play a critical bridge role between data engineering and data analysis. They work closely with data scientists to transform raw data into clean, reliable datasets that are ready for advanced analytics or modeling. At the same time, they collaborate with business stakeholders to understand reporting needs, ensuring that data models align with business goals. Regular communication and iterative feedback are key, as Analytics Engineers often gather requirements, build data pipelines, and adjust data products based on stakeholder input.

What is an analytics engineer?

An Analytics Engineer is a professional who bridges the gap between data engineering and data analysis. They are responsible for designing, building, and maintaining data models, pipelines, and analytics tools that enable organizations to make data-driven decisions. Analytics Engineers often work closely with data analysts and business stakeholders to ensure clean, reliable, and well-structured data is available for reporting and analysis. Their work typically involves using SQL, data transformation tools like dbt, and cloud data warehouses to create scalable and efficient data solutions.
What are the most commonly searched types of Analytics Engineer jobs in Houston, TX? The most popular types of Analytics Engineer jobs in Houston, TX are:
What are popular job titles related to Analytics Engineer jobs in Houston, TX? For Analytics Engineer jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Analytics Engineer jobs in Houston, TX look for? The top searched job categories for Analytics Engineer jobs in Houston, TX are:
What cities near Houston, TX are hiring for Analytics Engineer jobs? Cities near Houston, TX with the most Analytics Engineer job openings:
Analytics Engineer jobs near you
Infographic showing various Analytics Engineer job openings in Houston, TX as of August 2026, with employment types broken down into 72% Full Time, and 28% Contract. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $105,775 per year, or $50.9 per hour.

AI Cybersecurity Engineer Principal

Huntington

Houston, TX • On-site, Remote

Full-time

Posted 24 days ago

Job description

Description

The AI Cybersecurity Engineer Principle is responsible for designing, developing, and securing AI-driven solutions that enhance cybersecurity capabilities and enable safe enterprise adoption of artificial intelligence. This role bridges AI engineering, cybersecurity, and cloud platforms to deliver intelligent automation, advanced analytics, and secure application architectures. The position focuses on embedding security, governance, and risk controls into AI systems while driving innovation through agentic AI, automation, and data-driven decision-making.

Duties & Responsibilities

  • AI Solution Development: Design, build, and deploy AI/ML and generative AI applications to support cybersecurity operations and enterprise use cases.
  • Security Integration: Embed cybersecurity controls, secure coding practices, and data protection measures into AI applications and development pipelines.
  • Cyber Use Case Enablement: Develop solutions for threat detection, alert triage, vulnerability analysis, identity analytics, and risk scoring.
  • Automation & Agentic AI: Implement intelligent automation and agent-driven workflows to optimize cyber operations and reduce manual effort.
  • Data & Analytics: Engineer pipelines and analytics solutions for processing logs, telemetry, and security data to generate actionable insights.
  • Cloud & Platform Engineering: Deploy and manage scalable AI solutions in cloud-native environments using containers, APIs, and CI/CD pipelines.
  • System Integration: Integrate AI applications with enterprise and cybersecurity tools (SIEM, SOAR, IAM, data platforms).
  • Governance & Compliance: Ensure alignment with AI governance, regulatory requirements, and secure SDLC practices.
  • Collaboration: Partner with cybersecurity, engineering, data, and business teams to deliver secure, scalable AI capabilities

Basic Qualifications:

  • Bachelor's Degree or 4+ additional years of equivalent experience.
  • 8+ years of production support and design of Cyber Security technologies.
  • 8+ years of operational experience with security technologies.
  • 8+ years of implementing or utilizing technology lifecycles and best practices (SDLC lifecycle).

Preferred Qualifications

  • Experience in the implementation of cyber security tools (hardware and software)
  • Experience in participating and leading projects and implementing new technologies and solutions
  • Experience with agentic AI, Claude code, copilots, RAG architectures, and LLM orchestration frameworks
  • Experience implementing AI governance, model risk management, and security guardrails
  • Familiarity with cybersecurity platforms (SIEM, SOAR, EDR/XDR, vulnerability management, IAM tools)
  • Proficiency in modern programming languages such as Python, Java, .NET/C#, JavaScript/TypeScript, or Go, with strong API and backend development skills.
  • Demonstrated experience designing and developing RESTful APIs, microservices, and event-driven services to support enterprise AI and automation capabilities.
  • Strong hands-on software development experience with the ability to design, build, test, and deploy production-grade applications.
  • Ability to build and maintain a centralized AI agent registry that supports agent onboarding, unique agent identification, metadata management, ownership tracking, lifecycle status, versioning, and auditability.
  • Experience developing user interfaces and operational dashboards for monitoring, managing, and supporting AI agents, workflows, system health, and service activity.
  • Knowledge of data engineering, streaming analytics, and log/telemetry processing
  • Experience integrating applications with identity and access management platforms, including OAuth 2.0, OIDC, scoped tokens, service principals, managed identities, and role-based access controls.


Exempt Status: (Yes= not eligible for overtime pay) (No= eligible for overtime pay)

Yes

Workplace Type:

Remote

Our Approach to Office Workplace Type

Certain positions outside our branch network may be eligible for a flexible work arrangement. We're combining the best of both worlds: in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.

Huntington is an Equal Opportunity Employer.

Tobacco-Free Hiring Practice: Visit Huntington's Career Web Site for more details.

Note to Agency Recruiters: Huntington Bank will not pay a fee for any placement resulting from the receipt of an unsolicited resume. All unsolicited resumes sent to any Huntington Bank colleagues, directly or indirectly, will be considered Huntington Bank property. Recruiting agencies must have a valid, written and fully executed Master Service Agreement and Statement of Work for consideration.

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