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Mainframe Storage Remote Jobs in Kansas (NOW HIRING)

Data Engineer AI

Overland Park, KS · On-site +1

$108K - $130K/yr

Your mission is to build the pipelines that bridge our legacy on-prem systems (Mainframes, SQL ... Drive the efficiency of our data stack by optimizing storage and query performance in Snowflake ...

Mainframe Storage Remote information

See Kansas salary details

$8

$47

$65

How much do mainframe storage remote jobs pay per hour?

As of Jun 19, 2026, the average hourly pay for mainframe storage remote in Kansas is $47.73, according to ZipRecruiter salary data. Most workers in this role earn between $41.25 and $55.05 per hour, depending on experience, location, and employer.

What is the difference between Mainframe Storage Remote vs Mainframe Storage Technician?

AspectMainframe Storage RemoteMainframe Storage Technician
CredentialsCertifications in mainframe storage management, such as IBM Certified SpecialistCertifications in mainframe hardware and storage, often similar or overlapping
Work EnvironmentRemote access to mainframe systems, often in data centers or cloud environmentsOn-site or remote hardware maintenance and troubleshooting in data centers
Industry UsageUsed by organizations managing large-scale mainframe storage remotelyTypically on-site roles focusing on hardware and storage device maintenance
Search & ComparisonOften compared based on remote management skills vs on-site hardware skills

In summary, Mainframe Storage Remote focuses on managing mainframe storage systems remotely, often through cloud or network access, while Mainframe Storage Technician involves hands-on hardware maintenance and troubleshooting on-site or remotely. Both roles require similar certifications and are integral to mainframe storage management but differ mainly in work environment and daily tasks.

What are popular job titles related to Mainframe Storage Remote jobs in Kansas? For Mainframe Storage Remote jobs in Kansas, the most frequently searched job titles are:
What job categories do people searching Mainframe Storage Remote jobs in Kansas look for? The top searched job categories for Mainframe Storage Remote jobs in Kansas are:
What cities in Kansas are hiring for Mainframe Storage Remote jobs? Cities in Kansas with the most Mainframe Storage Remote job openings:
Infographic showing various Mainframe Storage Remote job openings in Kansas as of June 2026, with employment types broken down into 69% Full Time, and 31% Contract. Highlights an 100% Remote job distribution, with an average salary of $99,275 per year, or $47.7 per hour.
Data Engineer AI

Data Engineer AI

Sedgwick

Overland Park, KS • On-site, Remote

$108K - $130K/yr

Other

Posted 3 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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