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Insurance Data Engineer Jobs in Arizona (NOW HIRING)

Data Engineer AI

Phoenix, AZ · On-site +1

$113K - $136K/yr

Newsweek Recognizes Sedgwick as America's Greatest Workplaces National Top Companies Certified as a Great Place to Work ® Fortune Best Workplaces in Financial Services & Insurance Data Engineer AI ...

Data Engineer

Chandler, AZ

$116K - $140K/yr

Overview We are looking for a Data Engineer III to join an Enterprise Data team focused on ... We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and ...

Data Engineer

Tempe, AZ

$109K - $131K/yr

... insurance, and government entities. From billing and payments to mapping and proactive ... About the Role We're looking for a Data Engineer to join our Product Development - Business ...

Data Engineer

Tempe, AZ · On-site

$109K - $131K/yr

... insurance, and government entities. From billing and payments to mapping and proactive ... About the Role We're looking for a Data Engineer to join our Product Development - Business ...

Data Engineer

Tempe, AZ

$111K - $133K/yr

... insurance, and government entities. From billing and payments to mapping and proactive ... About the Role We're looking for a Data Engineer to join our Product Development - Business ...

Data Engineer

Tempe, AZ · On-site

$109K - $131K/yr

... insurance, and government entities. From billing and payments to mapping and proactive ... About the Role We're looking for a Data Engineer to join our Product Development - Business ...

We are looking for an accomplished and experienced Data Engineer with the following skills ... Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional ...

Principle Data Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Insurance, Health, Analytics, and Emerging businesses. Required Skills: Python, Pyspark/Spark, SQL, Data Lake (ON Prem or cloud) AWS, Snowflake. Job Summary: The Data Engineer's role is to play a ...

Senior Data Engineer

Phoenix, AZ

$105K - $143K/yr

If you are a data engineer who thrives at the intersection of technology and business, and enjoys ... Prior experience in healthcare or another highly regulated industry such as finance, insurance, or ...

Senior Data Engineer

Scottsdale, AZ · Remote

$106K - $145K/yr

PTZ Insurance Agency Ltd. POSITION TITLE: Sr. Data Engineer HOURS: Full Time/40 hours JOB DUTIES: Collaborate with business stakeholders to understand business strategy and needs, anticipate ...

Senior Data Engineer

Scottsdale, AZ · On-site +1

$106K - $145K/yr

PTZ Insurance Agency Ltd. POSITION TITLE: Sr. Data Engineer HOURS: Full Time/40 hours JOB DUTIES: Collaborate with business stakeholders to understand business strategy and needs, anticipate ...

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Insurance Data Engineer information

What health insurance covers Wegovy?

As an Insurance Data Engineer, understanding insurance coverage is essential. Coverage for Wegovy, a prescription weight management medication, varies by insurance plan and provider. Many health insurance plans, including some employer-sponsored plans and Medicare, may cover Wegovy if prescribed for approved indications, but prior authorization is often required.

What is the best cheapest insurance?

As an Insurance Data Engineer, evaluating the cheapest insurance involves analyzing data from multiple providers to identify affordable options that meet coverage needs. Comparing quotes, understanding policy details, and using data analysis tools can help find cost-effective insurance plans. However, the cheapest option may not always offer the best coverage, so balancing cost and coverage is essential.

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.

Does health insurance cover a pacemaker?

As an Insurance Data Engineer, you should know that health insurance typically covers pacemaker implantation and related procedures if deemed medically necessary, though coverage details vary by plan. Patients usually need prior authorization, and coverage may include device costs, surgery, and follow-up care. It is important to review specific policy terms and provider networks for accurate coverage information.

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.

Who does the cheapest insurance?

Insurance Data Engineers analyze data to help insurance companies identify cost-effective policies and pricing strategies. The cheapest insurance options typically depend on factors like coverage needs, customer profile, and provider discounts, rather than a specific role. Consumers should compare quotes from multiple providers to find the most affordable coverage.

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 Arizona? For Insurance Data Engineer jobs in Arizona, the most frequently searched job titles are:
What cities in Arizona are hiring for Insurance Data Engineer jobs? Cities in Arizona with the most Insurance Data Engineer job openings:
Infographic showing various Insurance Data Engineer job openings in Arizona as of June 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution.
Data Engineer AI

Data Engineer AI

Sedgwick

Phoenix, AZ • On-site, Remote

$113K - $136K/yr

Other

Posted 6 days ago


Sedgwick rating

7.5

Company rating: 7.5 out of 10

Based on 308 frontline employees who took The Breakroom Quiz

186th of 261 rated insurance


Job description

By joining Sedgwick, you'll be part of something truly meaningful. It’s what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there’s no limit to what you can achieve.

Newsweek Recognizes Sedgwick as America’s Greatest Workplaces National Top Companies

Certified as a Great Place to Work®

Fortune Best Workplaces in Financial Services & Insurance

Data Engineer AI

Role Overview

As a Senior Data Engineer within the Transformation Office, you are the hands-on architect of the data supply chain for our most advanced initiatives. You will be responsible for the "heavy lifting" required to fuel Data Science models and AI applications with high-fidelity data. Your mission is to build the pipelines that bridge our legacy on-prem systems (Mainframes, SQL Server, DB2) with our modern Snowflake environment and AWS/Azure AI stacks. You are a "day-one" builder who ensures that data is not just moved, but engineered for the specific requirements of model training, feature stores, and RAG-based AI systems.

Key Responsibilities

• Hybrid Data Pipeline Execution: Design and implement robust ETL/ELT pipelines to ingest data from legacy on-prem sources, AWS (S3/RDS), and Azure (Blob/SQL), centralizing it for consumption in Snowflake and AI services.

• Engineering for Data Science: Build and maintain Feature Stores and specialized datasets optimized for machine learning, ensuring Data Scientists have immediate access to clean, versioned, and statistically valid data.

• Engineering for AI (RAG & LLMs): Develop the data pipelines required for Generative AI, including the automated extraction, chunking, and loading of unstructured data into vector stores across AWS and Azure.

• Snowflake Power-User Execution: Act as the technical lead for our Snowflake data warehouse, implementing sophisticated data modeling, Snowpipe automation, and compute optimization to support high-concurrency AI workloads.

• Legacy "Back-Reach" Engineering: Execute non-invasive data extraction patterns to unlock mission-critical data from decades-old on-premise systems without disrupting core business operations.

• Multi-Cloud Orchestration: Manage complex, cross-platform data workflows using Airflow, Step Functions, or Azure Data Factory, ensuring the synchronization of data across our multi-cloud AI posture.

• IT & Security Diplomacy: Partner directly with central IT, Database Administrators, and Security teams to solve connectivity hurdles (PrivateLink, IAM, firewalls) and secure "license to operate" for new data flows.

• Data Quality for Model Integrity: Implement automated validation and observability layers to detect data drift and quality issues that could compromise the accuracy of production AI and Data Science models.

• Cost & Performance Management: Drive the efficiency of our data stack by optimizing storage and query performance in Snowflake, AWS, and Azure to manage the ROI of the Transformation Office.

• Direct Stakeholder Collaboration: Work as a dedicated engineering partner to MLOps and Data Science teams to rapidly iterate on data requirements for evolving AI use cases.

Qualifications

• Education: Bachelor’s degree in Computer Science, Data Engineering, or a related field is required. A Master’s degree is highly desirable.

• Proven Execution: 6+ years of hands-on data engineering experience, with a track record of building production-grade pipelines for Data Science and AI in multi-cloud environments.

• Snowflake Mastery: Expert-level proficiency in Snowflake architecture, including data sharing, performance tuning, and the integration of Snowflake with external cloud AI services.

• Multi-Cloud Proficiency: Advanced, hands-on knowledge of AWS (S3, Glue, Lambda) and Azure (Data Factory, Synapse) data services.

• Technical Stack: Mastery of Python, SQL, and PySpark. Deep experience with data orchestration and containerization (Docker).

• Legacy Expertise: Proven ability to interface with "old world" tech (on-premise SQL, Mainframe extracts, flat files) and transform it for modern cloud consumption.

• AI/DS Fluency: A strong understanding of the specific data needs for Machine Learning (feature engineering) and Generative AI (vectorization and embedding pipelines).

• Execution Mindset: A "get-it-done" attitude, capable of navigating enterprise bureaucracy and technical debt to ship code at the speed required by a Transformation Office.

#LI-TS1 #remote

Sedgwick is an Equal Opportunity Employer and a Drug-Free Workplace.

If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.

Sedgwick is the world’s leading risk and claims administration partner, which helps clients thrive by navigating the unexpected. The company’s expertise, combined with the most advanced AI-enabled technology available, sets the standard for solutions in claims administration, loss adjusting, benefits administration, and product recall. With over 33,000 colleagues and 10,000 clients across 80 countries, Sedgwick provides unmatched perspective, caring that counts, and solutions for the rapidly changing and complex risk landscape. For more, see sedgwick.com


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