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Data Classification Jobs in Seattle, WA (NOW HIRING)

Senior Data Engineer

Seattle, WA · On-site

$135K - $173K/yr

... data classification, and make recommendations to improve organization-wide data management. 5. Documentation and Procedures Create and manage documentation and appropriate procedures necessary to ...

... data classification, and make recommendations to improve organization-wide data management. 5. Documentation and Procedures Create and manage documentation and appropriate procedures necessary to ...

Senior Data Engineer

Seattle, WA · Hybrid

$135K - $173K/yr

... data classification, and make recommendations to improve organization-wide data management. 5. Documentation and Procedures Create and manage documentation and appropriate procedures necessary to ...

Senior Data Engineer

Seattle, WA · Hybrid

$135K - $173K/yr

... data classification, and make recommendations to improve organization-wide data management. 5. Documentation and Procedures Create and manage documentation and appropriate procedures necessary to ...

Comfort working within data classification and governance frameworks, and sound judgment about data sensitivity * Comfortable performing hands-on configuration and connectivity setup for AI ...

Comfort working within data classification and governance frameworks, and sound judgment about data sensitivity * Comfortable performing hands-on configuration and connectivity setup for AI ...

Cyber Data Protection/PKI Manager

Seattle, WA · On-site

$126K - $170K/yr

... Classification and Rights Management, Data Access Governance, Data Loss Prevention, Cloud Access Security Broker, Encryption, Certificate Lifecycle Management, Cloud Security, SaaS Security * 7+ ...

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Data Classification information

See Seattle, WA salary details

$52.3K

$187.8K

$277.1K

How much do data classification jobs pay per year?

As of Jul 15, 2026, the average yearly pay for data classification in Seattle, WA is $187,795.00, according to ZipRecruiter salary data. Most workers in this role earn between $151,900.00 and $193,500.00 per year, depending on experience, location, and employer.

What jobs make $1,000,000 a year?

In the field of data classification, high-paying roles such as Chief Data Officer or senior data science executives can earn around or above $1 million annually, especially in large corporations or tech firms. These positions typically require extensive experience, advanced skills in data management, and leadership responsibilities. Compensation often includes base salary, bonuses, and stock options.

What is the role of data classification?

Data classification is a key responsibility in data management roles, involving categorizing data based on sensitivity, importance, or usage to ensure proper handling and security. It helps organizations implement appropriate access controls, comply with regulations, and protect sensitive information effectively.

What are the key skills and qualifications needed to thrive in the Data Classification position, and why are they important?

To thrive in Data Classification, you need strong analytical skills, attention to detail, and a background in data management or information science, often supported by a relevant degree. Familiarity with data classification tools, data loss prevention (DLP) systems, and certifications such as Certified Information Systems Security Professional (CISSP) are commonly beneficial. Good communication, teamwork, and problem-solving skills help you excel in collaborating with IT, compliance, and business teams. These competencies are critical for accurately categorizing data, maintaining security standards, and ensuring regulatory compliance across an organization.

What is a Data Classification job?

A Data Classification job involves organizing and labeling data based on its sensitivity, importance, or type to ensure proper handling, security, and compliance. Professionals in this role categorize data according to predefined policies and frameworks, helping organizations safeguard sensitive information and optimize data management. They work closely with security, compliance, and IT teams to implement classification strategies and improve data governance.

What are the 4 types of data classification?

Data classification involves categorizing data based on its sensitivity and importance. The four common types are public, internal, confidential, and restricted data. Data classification helps organizations implement appropriate security measures and compliance protocols.

What are the typical challenges faced in a Data Classification role?

A common challenge in Data Classification is accurately identifying and categorizing large volumes of diverse and sometimes ambiguous data, which requires both technical proficiency and critical thinking. Balancing the need for data accessibility with strict security and compliance requirements can also pose difficulties. Collaboration with various departments, such as IT and legal, is often necessary to implement organization-wide classification policies and ensure consistent practices. By staying up-to-date with data protection regulations and evolving technology, professionals in this role can effectively address these challenges and contribute significantly to their organization’s information security strategy.

What is the highest paying data job?

Data scientists and data engineers are among the highest paying roles in data-related fields, often earning six-figure salaries depending on experience, location, and industry. Advanced skills in machine learning, big data tools, and programming languages like Python or SQL can further increase earning potential.
What are popular job titles related to Data Classification jobs in Seattle, WA? For Data Classification jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Data Classification jobs in Seattle, WA look for? The top searched job categories for Data Classification jobs in Seattle, WA are:
Infographic showing various Data Classification job openings in Seattle, WA as of July 2026, with employment types broken down into 1% As Needed, 68% Full Time, 27% Part Time, 1% Temporary, and 3% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $187,795 per year, or $90.3 per hour.
Sr. Data Engineer, Amazon PeopleInsights eXperience (APIX)

Sr. Data Engineer, Amazon PeopleInsights eXperience (APIX)

Amazon

Seattle, WA

$130K - $156K/yr

Full-time

Posted 19 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,968 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

Are you passionate about building scalable data infrastructure that powers critical business decisions. Do you thrive on solving complex data architecture challenges while mentoring engineers and driving technical excellence. If so, join the Amazon People Insights & Experience (APIX) team as a Senior Data Engineer!
We're transforming Amazon's fragmented people-data ecosystem into a centralized, AI-ready platform through the PXT Data Strategy-a multi-year program consolidating 20 data lakes with 13,000+ data sources into a unified Central Lakehouse serving 440+ data teams.

As a Senior Data Engineer, you'll be instrumental in building the data infrastructure that enables self-service analytics, AI-powered insights, and data governance at massive scale.
This is a hands-on technical leadership position where you will own team-level data architecture for flagship initiatives including the Central Lakehouse (achieving 100% Golden Dataset discoverability), Amazon Cortex (an intelligent data abstraction platform), and Clarity Metrics Marketplace (CMM)-reducing dataset onboarding time from 5-6 weeks to under 7 days. You'll architect solutions that serve 16,000+ HR professionals, operations leaders, and people managers across Amazon, directly impacting how the company makes data-driven workforce decisions.
We're looking for a top data engineer with deep expertise in distributed systems, data lake architectures, and a proven track record of delivering large-scale data solutions. You should excel at technical leadership, strategic thinking, and have genuine passion for building data infrastructure that scales to support hundreds of teams building metrics in parallel while maintaining Amazon's highest privacy and security standards.
Key job responsibilities
Own Team Data Architecture & Drive Technical Excellence
- Take ownership of team data architecture with system-wide perspective, anticipating data access patterns and proactively removing bottlenecks across the Central Lakehouse, Cortex, and CMM platforms
- Design and deliver exemplary, large-scale data solutions that are secure, maintainable, scalable, and extensible-enabling others to easily contribute and build upon your work
- Lead architectural improvements that simplify complex data systems, addressing deficiencies where your team's architecture bottlenecks other teams across PXT's 20 data lakes
- Make appropriate architectural trade-offs (build vs

buy, tiered storage strategies, data abstraction patterns) balancing short-term technology needs with long-term business requirements for Amazon's people data ecosystem
- Solve Ambiguous Problems & Lead Technical Strategy
- Work efficiently with limited guidance in ambiguous problem areas-where business problems are defined but technical strategies for Golden Dataset onboarding, metadata enrichment, and AI contextualization are not
- Lead identification and resolution of complex data engineering challenges including data duplication across 264 redundant warehouses, inconsistent metric definitions, and governance gaps across federated data lakes
- Influence team technical and business strategy for PXT Data Strategy workstreams, bringing perspective and context for current and future technology choices in AWS-first data platform adoption
- Build consensus when confronted with discordant views on data architecture approaches, demonstrating judgment on when to leverage existing solutions versus building new capabilities
- Deliver High-Impact Data Solutions at Amazon Scale
- Design and implement scalable data pipelines, ETL processes, and data abstraction layers supporting the Central Lakehouse (1,754+ Golden Datasets), Cortex Data Plane APIs, and self-service CMM capabilities
- Architect solutions handling high volumes of people data across 17,000+ applications, optimizing for data quality, availability, latency, security, performance, and integrity
- Reduce manual data preparation effort by 60-80% through intelligent data vending, contextualized metadata, and automated dataset onboarding workflows
- Deliver data infrastructure supporting AI-powered insights (Clarity Assist, Quick Suite integration) with >90% query accuracy and <7 day metric creation timelines
- Drive Engineering Best Practices & Governance
- Set and enforce standards for data discovery, naming conventions, operational excellence, data security, and code quality across PXT data engineering teams
- Lead implementation of systematic governance through integration with FPDS primitives (DISAPERE, Maple, UBX), enabling policy-driven data classification, automated depersonalization, and cell-level access control
- Collaborate with AWS BDT, Security, and FPDS teams to influence roadmaps for SageMaker Unified Studio (SMUS), Andes External Tables, and Quick Suite integration-addressing 95+ identified feature gaps
- Ensure all data solutions comply with Amazon's privacy standards, GDPR/DSAR requirements, and Red certification processes for sensitive people data
- Mentor Engineers & Elevate Team Capabilities
- Actively mentor and coach data engineers and analysts across the organization, improving technical knowledge of distributed systems, data lake architectures, and AWS data services
- Provide technical assessments and guidance for DE II and DE III promotion candidates, helping team members grow their careers
- Lead design reviews for your team's data architecture and actively participate in design reviews of related software and data systems across PXT
- Demonstrate technical influence over 1-2 teams through collaborative development efforts and increasing productivity through data engineering best practices
- Stay Current with Evolving Data Technologies
- Master the constantly evolving AWS data toolkit including Andes, Athena, Glue, Redshift, SageMaker Unified Studio, and Quick Suite-adopting AWS-first approaches while retiring bespoke solutions
- Evaluate and integrate emerging technologies for data lake management, GenAI contextualization (Model Context Protocols, vector embeddings), and serverless data engineering patterns
- Pioneer privacy-first architecture patterns and AI-ready data infrastructure that positions PXT as AWS QuickSight's #1 customer and establishes foundations for external AWS product offerings
About the team
Meet the behind the scenes team that enables our Operations and Human Resource Leaders to make informed decisions. The Amazon Clarity team builds reporting and analytics tools for our teams that fulfill customer promise every day. Whether it is Fulfillment Center team that delivers your Prime order in two days, our Amazon Locker team that lets you pick up your package anytime that is convenient for you, our Prime Now team getting you lunch in under an hour, or one of many more, the PeopleInsight group is there providing people metrics along the employee life-cycle for our global operations businesses.

In addition to standard reporting, we leverage predictive analytics using ML to help our leaders focus their efforts in ways that will engage, retain and grow their associates.


What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US