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Insurance Data Engineer Jobs in Houston, TX (NOW HIRING)

Data Support Engineer

Houston, TX

$109K - $131K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... oriented Data Support Engineer to join our dynamic Vision Data Engineering team in Houston ... Life insurance * Short-term & Long-term disability All your information will be kept confidential ...

Data Scientist - Operations Research

Houston, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The ideal candidate has advanced education in science, engineering, computer science, statistics ... D, and disability insurance. Accruals for PTO and Extended Illness Bank, plus paid holidays ...

Data Scientist - Operations Research

Houston, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The ideal candidate has advanced education in science, engineering, computer science, statistics ... D, and disability insurance. Accruals for PTO and Extended Illness Bank, plus paid holidays ...

Data Scientist - Operations Research

Houston, TX

$106K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The ideal candidate has advanced education in science, engineering, computer science, statistics ... and disability insurance. • Accruals for PTO and Extended Illness Bank, plus paid holidays ...

Data Scientist - Operations Research

Houston, TX

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The ideal candidate has advanced education in science, engineering, computer science, statistics ... and disability insurance. • Accruals for PTO and Extended Illness Bank, plus paid holidays ...

Showing results 41-60

Insurance Data Engineer information

See Houston, TX salary details

$42.5K

$123.9K

$169.5K

How much do insurance data engineer jobs pay per year?

As of Aug 12, 2026, the average yearly pay for insurance data engineer in Houston, TX is $123,876.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,300.00 and $131,300.00 per year, depending on experience, location, and employer.

What is an insurance data engineer?

Insurance Data Engineers are professionals who design, build, and maintain data systems that support the needs of insurance companies. They are responsible for collecting, organizing, and processing large amounts of data from various sources to enable accurate risk assessment, pricing, claims analysis, and regulatory compliance. Their work helps insurers make data-driven decisions, improve efficiency, and enhance customer experiences by leveraging modern data technologies.

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

To thrive as an Insurance Data Engineer, you need strong expertise in data modeling, ETL processes, and a solid understanding of insurance data structures, typically supported by a degree in computer science, data engineering, or a related field. Proficiency with SQL, Python, big data platforms (like Hadoop or Spark), and experience with cloud data solutions such as AWS or Azure are commonly required, along with certifications like AWS Certified Data Analytics or Google Cloud Data Engineer. Excellent problem-solving, communication, and collaboration skills help you bridge technical and business needs while ensuring data quality. These abilities are essential for building robust data pipelines and enabling accurate data-driven decision making within insurance organizations.

What is the difference between Insurance Data Engineer vs Data Analyst in the insurance industry?

AspectInsurance Data EngineerData Analyst
Required CredentialsBachelor's in Computer Science, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentDevelops data pipelines, manages databases, works with big data toolsInterprets data, creates reports, visualizes insights
Employer & Industry UsageInsurance companies, tech firms in insuranceInsurance firms, consulting agencies, analytics companies

Insurance Data Engineers focus on building and maintaining data infrastructure, while Data Analysts interpret data to provide insights. Both roles are essential in the insurance industry but serve different functions in data management and analysis.

How does an insurance data engineer typically collaborate with actuarial and underwriting teams?

Insurance Data Engineers work closely with actuarial and underwriting teams to ensure that the data infrastructure supports accurate risk assessment and pricing models. They often translate business requirements from these teams into technical specifications, build data pipelines to source and clean relevant data, and assist in implementing predictive analytics tools. Regular communication and collaboration are essential, as data engineers help bridge the gap between raw data and actionable insights for decision-making. This teamwork not only streamlines workflow but also enables continuous improvement of insurance products and customer experience.
What are popular job titles related to Insurance Data Engineer jobs in Houston, TX? For Insurance Data Engineer jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Insurance Data Engineer jobs in Houston, TX look for? The top searched job categories for Insurance Data Engineer jobs in Houston, TX are:
What cities near Houston, TX are hiring for Insurance Data Engineer jobs? Cities near Houston, TX with the most Insurance Data Engineer job openings:
Infographic showing various Insurance Data Engineer job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, and 4% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $123,876 per year, or $59.6 per hour.

Data Support Engineer

Vitol

Houston, TX

$109K - $131K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago


Job description

Company Description

Vitol is a leader in energy and commodities. Vitol produces, manages and delivers energy and commodities to consumers and industry worldwide. In addition to its primary business of trading, Vitol is invested in infrastructure globally, with $10+billion invested in long-term assets.

Vitol’s customers include national oil companies, multinationals, leading industrial companies and utilities. Founded in Rotterdam in 1966, today Vitol serves its customers from some 40 offices worldwide. Revenues in 2024 were $331bn.

Our people are our business. Talent is precious to us and we create an environment in which individuals can reach their full potential, unhindered by hierarchy. Our team comprises more than 65+ nationalities and we are committed to developing and sustaining a diverse work force. Learn more about us here.

This Role is located in Houston, TX - In office 5x a week

Job Description

We are seeking a proactive and detail-oriented Data Support Engineer to join our dynamic Vision Data Engineering team in Houston, supporting mission-critical data pipelines in a fast-paced energy trading environment. As part of a global support team, you will provide Level 1 (L1) and Level 2 (L2) support, ensuring high availability, reliability, and performance of our data platforms. You will collaborate closely with application development teams, and business users across multiple regions to resolve and document incidents, manage service requests, and drive continuous improvement in support processes.

This role offers the opportunity to work in a collaborative, global environment at the intersection of technology and energy trading, with significant exposure to business operations and the latest data platform technologies.

Key Responsibilities:

  • Provide L1 and L2 support for data pipelines, including incident triage, troubleshooting, and resolution.
  • Monitor data pipeline health, performance, and data flows using monitoring tools and dashboards.
  • Respond to and resolve user queries, issues, and service requests in a timely manner, maintaining high customer satisfaction.
  • Escalate complex issues to L3 support or development teams, ensuring clear documentation and communication.
  • Perform routine operational tasks such as data monitor digest failure notifications, vendor credentials management, batch job monitoring, and data integrity checks.
  • Collaborate with business users to understand requirements and provide guidance on data related functionality and best practices.
  • Maintain and update support documentation, knowledge bases, and runbooks.
  • Identify recurring issues and contribute to root cause analysis and problem management.
  • Support incident and change management processes in line with best practices.
  • Participate in an on-call rotation and provide after-hours support as required.
Qualifications

Required:

  • Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field (or equivalent experience).
  • 3+ years of experience in application support, preferably within the energy trading, financial services, or data-intensive industries.
  • Strong understanding of L1/L2 support processes, incident management, and service desk operations.
  • Experience supporting data flows & processes (e.g., data warehouses, ETL pipelines, reporting tools, or real-time data feeds).
  • Ability to understand basic Python code and write scripts to automate data quality checks.
  • Proficiency with SQL for data investigation and troubleshooting.
  • Familiarity with Linux/Unix and Windows operating systems.
  • Experience with monitoring tools such as Datadog, Splunk, Grafana, AppDynamics, or similar.
  • Strong analytical and problem-solving skills, with the ability to work under pressure and prioritize effectively.
  • Excellent communication skills, both written and verbal, with the ability to interact with technical and non-technical stakeholders.
  • Customer-focused mindset with a commitment to delivering high-quality support.
  • Ability to work effectively as part of a distributed, worldwide team.

Preferred:

  • Experience in the energy trading sector or with trading platforms.
  • Experience working with AI agents
  • Familiarity with scripting languages (e.g., Python, Shell, PowerShell) for automation and troubleshooting.
  • Exposure to cloud platforms (e.g., AWS, Azure) and data platform services.
  • Experience with ticketing systems (e.g., ServiceNow, Jira Service Desk).

Additional Information

Comprehensive benefit coverage includes:

  • Medical
  • Dental
  • Vision
  • Paid Vacation
  • 401k with company contributions
  • Life insurance
  • Short-term & Long-term disability

All your information will be kept confidential according to EEO guidelines.