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

Lead Data Engineer Location: Houston, TX Duration: Full-time Salary: $110k/yr to $120k/yr Day to ... All compensation and benefits, including but not limited to medical insurance, retirement plans ...

SR Data Engineer

Houston, TX · On-site +1

$109.30K - $131.20K/yr

Summary/Objective Alliance Technical Group is seeking an experienced Senior Data Engineer to design ... Employee Benefits: Key Benefits Include: - Medical, Dental, and Vision Insurance - Flexible ...

Azure Data Engineer

Houston, TX · On-site

$105.60K - $126.90K/yr

Azure Data Engineer Houston TX - Onsite from day 1 Project Overview: New project- credit card ... You will independently drive design decisions to insure the necessary health of the overall ...

Big data engineer

Houston, TX

$53.25 - $70.50/hr

... Science, Insurance, legal, healthcare, among others. It also offers outsourcing, consulting ... Big Data Engineer Location: Houston, TX- locals highly preferred Duration: Through 3/31/2017 Notes:

Senior Data Engineer

Houston, TX · Remote

$108.50K - $147.40K/yr

Job SummaryThe Data Engineer - Asset Management Analytics supports internal Asset Management and ... banking, insurance, fintech, credit/loan portfolios, structured finance). * CFA (Chartered ...

Senior Data Engineer

Houston, TX · On-site +1

$101.20K - $137.50K/yr

Job Summary The Data Engineer - Asset Management Analytics supports internal Asset Management and ... banking, insurance, fintech, credit/loan portfolios, structured finance). * CFA (Chartered ...

Develop data pipelines and feature engineering using Spark / Delta Lake * Enable governed, zero ... medical insurance, dental insurance, vision insurance, 401(k) retirement plan, life insurance ...

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Insurance Data Engineer information

See Spring, TX salary details

$39.6K

$115.4K

$158K

How much do insurance data engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for insurance data engineer in Spring, TX is $115,433.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,900.00 and $122,400.00 per year, depending on experience, location, and employer.

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.

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 Insurance Data Engineers?

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 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.

What are popular job titles related to Insurance Data Engineer jobs in Spring, TX? For Insurance Data Engineer jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Insurance Data Engineer jobs in Spring, TX look for? The top searched job categories for Insurance Data Engineer jobs in Spring, TX are:
What cities near Spring, TX are hiring for Insurance Data Engineer jobs? Cities near Spring, TX with the most Insurance Data Engineer job openings:
Lead Data Engineer

$110K - $120K/yr

Other

Medical, Retirement, PTO

Posted 20 days ago


Job description

Title: Lead Data Engineer
Location: Houston, TX
Duration: Full-time
Salary: $110k/yr to $120k/yr


Day to day:



  • Design and implement reliable data pipelines to integrate disparate data sources into a single Data Lakehouse.

  • Design and implement data quality pipelines to ensure data correctness and build trusted datasets.

  • Design and implement a Data Lakehouse solution that accurately reflects business operations.

  • Assist with data platform performance tuning and physical data model support, including partitioning and compaction.

  • Provide guidance in data visualizations and reporting efforts to ensure solutions are aligned with business objectives.

  • Automate and optimize the data lifecycle, find insights from raw data, and apply

  • DevOps principles to data pipelines.


Must Haves:



  • Experience: 5+ years as a Data Engineer focused on designing and maintaining data pipeline architectures.

  • Programming: 5+ years of in-depth experience with Python and SQL (specifically T-SQL).

  • Cloud & Data Stack: Hands-on experience with AWS and Snowflake.


This is a direct hire opportunity. The selected candidate will be employed directly by our client. All compensation and benefits, including but not limited to medical insurance, retirement plans, paid time off, and other perks, will be provided by the client in accordance with their internal policies and subject to applicable laws and eligibility requirements.