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Remote Amazon Data Engineer Jobs in Kansas (NOW HIRING)

Data Engineer AI

Overland Park, KS · On-site +1

$108K - $130K/yr

You are a "day-one" builder who ensures that data is not just moved, but engineered for the ... LI-TS1 #remote Sedgwick is an Equal Opportunity Employer and a Drug-Free Workplace. If you're ...

Enable self-service analytics and reporting using Amazon QuickSight * Build and operate data ... A fully remote work environment with flexibility and autonomy. * The opportunity to grow with a ...

Location - We are flexible on remote working from home, if you are located in the USA and reside in ... on data engineering and data science. * Experience in building data pipelines and managing large ...

CrowdStrike is looking for a Principal Data Engineer with deep expertise in Large Language Models ... Contributions to open-source projects related to data or AI/ML. #LI-RC1 #LI-Remote Benefits of ...

Senior Data Software Engineer

Kansas, KS · On-site +1

$108K - $142K/yr

Location - We are flexible on remote working from home, if you are located in the USA and reside in ... on data engineering and data science. * Experience in building data pipelines and managing large ...

Amazon Connect Architect

Canada, KY · Remote

$54 - $71.25/hr

... data workflows. Responsibilities * Architect end-to-end AWS-based solutions for Amazon Connect ... Lead cross-functional engineering, DevOps, and product teams to deliver complex solutions * Align ...

Amazon Connect Architect

Canada, KY · Remote

$54 - $71.25/hr

... data workflows. Responsibilities * Architect end-to-end AWS-based solutions for Amazon Connect ... Lead cross-functional engineering, DevOps, and product teams to deliver complex solutions * Align ...

$54 - $71.25/hr

... data workflows. Responsibilities * Architect end-to-end AWS-based solutions for Amazon Connect ... Lead cross-functional engineering, DevOps, and product teams to deliver complex solutions * Align ...

$54 - $71.25/hr

... data workflows. Responsibilities * Architect end-to-end AWS-based solutions for Amazon Connect ... Lead cross-functional engineering, DevOps, and product teams to deliver complex solutions * Align ...

... data infrastructure, and real-time decisioning ... Watch our talk at Amazon Tech Talks: StackAdapt is a Remote First company, we are open to ...

StackAdapt is a Remote First company, we are open to candidates located anywhere in North America ... Watch our talk at Amazon Tech Talks: What you'll be doing: * Leading a team that builds solutions ...

... join our engineering team as we continue to expand our data science efforts. Our platform is ... Watch our talk at Amazon Tech Talks: StackAdapt is a remote-first company, and we are open to ...

You'll work alongside a Staff Data Engineer (who owns the data foundation) and report to the ... site, remote, or dispersed across global networks. Our platform automates network discovery ...

Watch our talk at Amazon Tech Talks: StackAdapt is a Remote First company, we are open to ... Collaborate with stakeholders from Data Science, Product & Design and other senior engineers across ...

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Remote Amazon Data Engineer information

Can I work remotely as a data engineer?

Remote work is common for data engineers, including those working with companies like Amazon. Many data engineering roles involve tasks such as data pipeline development, database management, and cloud platform usage, which can often be performed remotely with the right skills and tools. However, some positions may require on-site presence for collaboration or specific project needs.

How much do Amazon data engineers make?

Amazon data engineers typically earn between $100,000 and $150,000 annually, depending on experience, location, and skill level. Senior roles or those with expertise in cloud platforms and big data tools may earn higher salaries, often exceeding $160,000.

What does a Remote Amazon Data Engineer do?

A Remote Amazon Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and databases for Amazon or companies using Amazon Web Services (AWS). They work remotely to process large volumes of data, ensure data quality, and enable efficient data analysis. Their tasks typically include extracting data from various sources, transforming it into usable formats, and loading it into data warehouses or analytics platforms. They often use AWS tools such as Redshift, Glue, S3, and Lambda to manage infrastructure and automate workflows. Strong programming skills in languages like Python or SQL are essential for this role.

What is the difference between Remote Amazon Data Engineer vs Remote Amazon Data Analyst?

AspectRemote Amazon Data EngineerRemote Amazon Data Analyst
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentDesigning data pipelines, managing ETL processesInterpreting data, creating reports and dashboards
Employer & Industry UsageTech companies, e-commerce, cloud servicesRetail, marketing, e-commerce
Common Search & ComparisonFocus on data infrastructure and pipelinesFocus on data insights and reporting

The main difference between a Remote Amazon Data Engineer and a Remote Amazon Data Analyst lies in their roles. Data Engineers build and maintain data pipelines and infrastructure, requiring technical skills in data architecture. Data Analysts interpret data to generate insights, focusing on analysis and reporting. Both roles are essential in data-driven companies but serve different functions within the data ecosystem.

Does Amazon hire for remote work?

Amazon offers remote work opportunities for various roles, including data engineers, depending on the position and team needs. Many remote positions require relevant skills, such as experience with cloud platforms like AWS, and may involve flexible schedules or specific technical requirements.

What are some common challenges faced by Remote Amazon Data Engineers, and how can they be addressed?

Remote Amazon Data Engineers often encounter challenges related to collaborating across time zones and ensuring clear communication with global teams. Effective use of collaboration tools, regular virtual meetings, and clear documentation can help bridge these gaps. Additionally, managing large-scale data pipelines on AWS requires staying updated on best practices for security, scalability, and cost optimization. Proactively participating in team stand-ups and engaging in continuous learning about AWS services can significantly enhance productivity and project outcomes.

What engineers make $500,000?

Senior data engineers, especially those working at large tech companies like Amazon, can earn $500,000 or more annually, including base salary, bonuses, and stock options. Achieving this level typically requires extensive experience, advanced skills in data architecture, cloud platforms, and programming, as well as a track record of impactful projects.

What are the key skills and qualifications needed to thrive as a Remote Amazon Data Engineer, and why are they important?

To thrive as a Remote Amazon Data Engineer, you need strong expertise in data modeling, ETL development, SQL, and programming languages such as Python or Java, typically supported by a degree in computer science or a related field. Familiarity with AWS services like Redshift, S3, Glue, and data pipeline tools, as well as certifications such as AWS Certified Data Analytics, are highly valued. Excellent problem-solving, communication, and self-management skills help remote engineers collaborate effectively and deliver reliable data solutions. These abilities are crucial for ensuring robust, scalable data infrastructure and supporting data-driven decision-making in a distributed work environment.
What are the most commonly searched types of Amazon Data Engineer jobs in Kansas? The most popular types of Amazon Data Engineer jobs in Kansas are:
What are popular job titles related to Remote Amazon Data Engineer jobs in Kansas? For Remote Amazon Data Engineer jobs in Kansas, the most frequently searched job titles are:
What job categories do people searching Remote Amazon Data Engineer jobs in Kansas look for? The top searched job categories for Remote Amazon Data Engineer jobs in Kansas are:
What cities in Kansas are hiring for Remote Amazon Data Engineer jobs? Cities in Kansas with the most Remote Amazon Data Engineer job openings:
Data Engineer AI

Data Engineer AI

Sedgwick

Overland Park, KS • On-site, Remote

$108K - $130K/yr

Other

Posted 2 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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