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Insurance Data Engineer Jobs in Rensselaer, NY (NOW HIRING)

Data Engineer - GP Fund Solutions Where Data Meets Decision-Making. We turn numbers into insights ... Company-Paid Life Insurance & 401(k). * Generous PTO, Sick Time & Paid Holidays. * Hybrid ...

Data Engineer

Latham, NY · On-site

$95K - $115K/yr

Data Engineer GP Fund Solutions Where Data Meets Decision-Making. We turn numbers into insights ... Company-Paid Life Insurance & 401(k). * Generous PTO, Sick Time & Paid Holidays. * Hybrid ...

Data Engineer

Latham, NY · On-site

$95K - $115K/yr

Data Engineer - GP Fund Solutions Where Data Meets Decision-Making. We turn numbers into insights ... Company-Paid Life Insurance & 401(k). * Generous PTO, Sick Time & Paid Holidays. * Hybrid ...

Data Engineer

Albany, NY

$113K - $136K/yr

Data Engineer Employment Type: Full-Time, Mid-level Department: Business Intelligence CGS is ... Therefore, we offer a comprehensive benefits package: -Health, Dental, and Vision -Life Insurance ...

Data Engineer

Albany, NY · On-site

$112K - $152K/yr

Data Engineer Employment Type: Full-Time, Mid-level Department: Business Intelligence CGS is ... Therefore, we offer a comprehensive benefits package: -Health, Dental, and Vision -Life Insurance ...

Sr. Data Engineer

Albany, NY · On-site

$113K - $136K/yr

Sr. Data Engineer Employment Type: Full-Time, Mid-level Department: Business Intelligence CGS is ... Therefore, we offer a comprehensive benefits package: -Health, Dental, and Vision -Life Insurance ...

Senior Data Engineer

Latham, NY · On-site

$115K - $140K/yr

Senior Data Engineer GP Fund Solutions Where Data Meets Decision-Making. We turn numbers into ... Company-Paid Life Insurance & 401(k). * Generous PTO, Sick Time & Paid Holidays. * Hybrid ...

Senior Data Engineer

Latham, NY · On-site

$115K - $140K/yr

Senior Data Engineer - GP Fund Solutions Where Data Meets Decision-Making. We turn numbers into ... Company-Paid Life Insurance & 401(k). * Generous PTO, Sick Time & Paid Holidays. * Hybrid ...

Senior Data Engineer - GP Fund Solutions Where Data Meets Decision-Making. We turn numbers into ... Company-Paid Life Insurance & 401(k). * Generous PTO, Sick Time & Paid Holidays. * Hybrid ...

This role applies data analysis techniques to insurance data to improve risk segmentation and rate ... Work with large, structured and semistructured datasets using SQL and analytical programming ...

Apply insurance domain knowledge (e.g., coverage, exposure, underwriting rules, regulatory ... Advanced proficiency in analytical programming languages and tools (e.g., SQL, Python, R)

... insurance, no-cost-to-you vision insurance for you and your qualified dependents. We are also ... This role operates at the intersection of data science, data engineering, cloud analytics platforms ...

... insurance, no-cost-to-you vision insurance for you and your qualified dependents. We are also ... This role operates at the intersection of data science, data engineering, cloud analytics platforms ...

Data Analyst 2 - 78132

Albany, NY · On-site

$86K - $109K/yr

... or applications in programming languages to conduct analyses; creates written reports and ... Experience in Insurance, Medicaid preferred, 1 year of SQL experience working with large datasets ...

We're allergic to bureaucracy, thrive on innovation, and embrace data-driven decisions. If you love ... insurance Health insurance Life insurance Unlimited Paid time off Professional development ...

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Insurance Data Engineer information

See Rensselaer, NY salary details

$44.2K

$128.8K

$176.2K

How much do insurance data engineer jobs pay per year?

As of Jul 25, 2026, the average yearly pay for insurance data engineer in Rensselaer, NY is $128,788.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,700.00 and $136,500.00 per year, depending on experience, location, and employer.

How much do insurance engineers make?

Insurance data engineers typically earn a median salary ranging from $80,000 to $120,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in data pipelines, cloud platforms, and programming languages like Python or SQL can command higher salaries. Compensation may also include benefits such as bonuses and professional development opportunities.

What engineers make $500,000?

Senior data engineers, including those working in specialized fields like insurance data engineering, can earn $500,000 or more annually, especially with extensive experience, advanced skills in cloud platforms, and leadership roles. High compensation is often associated with seniority, complex data systems, and working in competitive markets or large organizations.

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 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.

Is AI replacing data engineers?

AI is transforming the role of data engineers by automating routine tasks such as data cleaning and integration, but it does not replace the need for skilled professionals to design, manage, and oversee data infrastructure. Data engineers are essential for building scalable data pipelines, ensuring data quality, and implementing AI solutions effectively. Their expertise remains critical in managing complex data environments and integrating AI tools into business processes.

What engineers make 300,000 a year?

Senior data engineers, including those working in specialized fields like insurance data engineering, can earn $300,000 or more annually, especially with extensive experience, advanced skills in SQL, Python, cloud platforms, and certifications. High-level roles often involve leadership, complex data architecture, and strategic decision-making, typically in large organizations or with specialized expertise.
What job categories do people searching Insurance Data Engineer jobs in Rensselaer, NY look for? The top searched job categories for Insurance Data Engineer jobs in Rensselaer, NY are:
What cities near Rensselaer, NY are hiring for Insurance Data Engineer jobs? Cities near Rensselaer, NY with the most Insurance Data Engineer job openings:
Data Engineer

$95K - $115K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 24 days ago


Job description

Data Engineer- GP Fund Solutions

Where Data Meets Decision-Making. We turn numbers into insights that drive client success.

Join GP Fund Solutions (GPFS) - a people-first fund administrator serving clients across the US, UK, and EU. We offer a collaborative culture, real career growth, and benefits that invest in your future.

What You'll Do:

  • Assist with the development and maintenance of the core data warehouse structure and help with the transition to a lakehouse.
  • Help evaluate existing Snowflake workloads and identify candidates for migration, optimization, or hybrid operation.
  • Identify performance issues and assist with solution plans.
  • Assist with the development and maintenance of dbt models across staging, intermediate, mart, and semantic layers, following established project structure, testing, and documentation standards.
  • Help build and maintain data pipelines that ingest data from source systems into Snowflake, collaborating with platform and analytics teams on requirements and priorities.
  • Write and optimize SQL transformations for performance, readability, and maintainability within Snowflake.
  • Contribute to data quality and reliability efforts, including schema validation, source freshness checks, row-level testing, and pipeline monitoring.
  • Participate in CI/CD processes for data, including automated testing, code review, and deployment practices using Git-based workflows.
  • Contribute to Snowflake and cloud infrastructure configuration, including warehouse sizing, access patterns, and integration with surrounding services, under the guidance of senior engineers.
  • Support orchestration workflows and data pipeline scheduling, helping ensure pipelines run reliably and recover gracefully from failures.
  • Participate in design reviews, offering input on implementation approaches and learning from senior engineers' architectural decisions.
  • Troubleshoot and resolve pipeline and data quality issues, conduct root cause analysis and implement fixes.
  • Document work clearly, including data models, pipelines, and operational runbooks, so the broader team can understand and maintain what you build.

What We're Looking For:

  • 3+ years of experience in data engineering, analytics engineering, or a closely related technical field.
  • Hands-on experience with Snowflake, including writing performant SQL, understanding warehouse behavior, and working with Snowflake's access and security model.
  • Understanding of dimensional modeling, data marts, data quality controls, and enterprise reporting needs.
  • Hands-on experience with dbt, including building and testing models, using macros, and following layered project structures.
  • Solid understanding of data modeling concepts, including dimensional modeling and common transformation patterns.
  • Proficiency in SQL for analytical and transformation workloads, including debugging and performance along with familiarity with common tools and practices used to do so.
  • Experience with Git-based version control and collaborative development workflows.
  • Familiarity with building or supporting data pipelines for analytics and/or AI/ML use cases.
  • Exposure to CI/CD practices for data, cloud infrastructure, and orchestration tooling.

Why GPFS?

  • Strong training plans and materials provided.
  • Competitive Medical, Dental & Vision Insurance.
  • Company-Paid Life Insurance & 401(k).
  • Generous PTO, Sick Time & Paid Holidays.
  • Hybrid Scheduling after probation period.
  • Inclusive, team-oriented culture where people come first.

At GPFS, every voice matters and every win is shared. We're raising the bar in our industry-come grow with us!


#LI-GP1

Employment Type: FULL_TIME