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Data Anonymization Jobs in Missouri (NOW HIRING)

Drive the adoption of best practices in AI privacy, security, and compliance, including data anonymization, secure data handling, and regulatory adherence. * Optimize platform performance ...

New

Implement data anonymization, quality checks, lineage, and controls for handling sensitive information. * Provide Technical Leadership: Offer hands‑on leadership across data engineering projects.

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Lead Service Management Engineer

O Fallon, MO · On-site

$95K - $126K/yr

Implement data anonymization, quality checks, lineage, and controls for handling sensitive information.* Provide Technical Leadership: Offer handson leadership across data engineering projects.

Data Anonymization information

What is data anonymization?

Data anonymization is the process of transforming personal or sensitive data so that individuals cannot be identified, either directly or indirectly. This is typically achieved by removing or encrypting identifiers such as names, addresses, or social security numbers, and sometimes by aggregating data. The goal is to protect privacy while still allowing the data to be used for analysis or research. Data anonymization is crucial in complying with privacy regulations like GDPR and HIPAA. Properly anonymized data helps organizations minimize risk while making valuable data available for insights and decision-making.

What are the key skills and qualifications needed to thrive in data anonymization, and why are they important?

To thrive in Data Anonymization, you need expertise in data privacy principles, knowledge of statistical methods, and a background in computer science, information security, or related fields. Familiarity with tools like ARX, sdcMicro, and programming languages such as Python or R, as well as understanding of regulations like GDPR, is typically required. Strong analytical thinking, attention to detail, and effective communication skills set professionals apart in this field. These competencies are crucial for ensuring sensitive information is protected while maintaining data utility for analysis and compliance.

What are some common challenges faced by professionals working in data anonymization roles?

Professionals in data anonymization often encounter challenges such as balancing data utility with privacy, ensuring compliance with evolving data protection regulations, and addressing the risk of re-identification. The work typically involves collaborating closely with data engineers, analysts, and legal teams to determine the appropriate anonymization techniques for various datasets. Staying updated on new privacy tools and methodologies is crucial, as is adapting processes to fit the unique needs of each project or organization.

What is the difference between Data Anonymization vs Data Masking?

AspectData AnonymizationData Masking
PurposeTo permanently remove or alter identifiable information to protect privacyTo temporarily hide sensitive data for testing or training
MethodData is irreversibly transformedData is reversibly masked or obscured
Use CasesData sharing, privacy compliance, anonymized analyticsTesting, development, user training
Impact on DataData becomes non-identifiable and unusable for original purposesData remains usable but obscured

While both Data Anonymization and Data Masking aim to protect sensitive information, Data Anonymization permanently alters data to prevent re-identification, making it suitable for privacy compliance and sharing. Data Masking temporarily obscures data for testing or training, allowing data usability while protecting sensitive details.

How does data anonymization work?

Data anonymization involves transforming personal data to prevent identification of individuals by removing or masking identifiable information such as names, addresses, or social security numbers. Techniques include data masking, pseudonymization, and generalization, often implemented using specialized tools and following privacy standards like GDPR or HIPAA. Data anonymization is essential for protecting privacy while enabling data analysis and sharing.

What are popular job titles related to Data Anonymization jobs in Missouri?

For Data Anonymization jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Data Anonymization jobs in Missouri look for?

The top searched job categories for Data Anonymization jobs in Missouri are:

Infographic showing various Data Anonymization job openings in Missouri as of June 2026, with employment types broken down into 1% As Needed, 88% Full Time, and 11% Part Time. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Senior AI Engineer - AI Platform

ClickUp

California, MO • On-site

$130 - $160/hr

Other

Posted 3 days ago

New


Job description

Role Overview

We are seeking a skilled and experienced Senior AI Engineer – AI Platform to join our ClickUp Engineering team. In this role, you will play a critical part in both building the core AI platform and directly applying large language models (LLMs) to deliver intelligent features across ClickUp. You will focus on backend systems that enable scalable, reliable, and secure AI-powered capabilities, while also working hands‑on with LLMs to solve real user problems and drive product innovation.

Key Responsibilities
  • Architect, design, and implement scalable AI platform services that support the deployment, orchestration, and lifecycle management of LLMs and other AI models.
  • Apply LLMs and other AI technologies directly to build and enhance ClickUp’s intelligent features, working closely with product and engineering teams to deliver impactful solutions.
  • Build and maintain robust APIs and backend systems that enable seamless integration of AI‑powered features into ClickUp’s core platform.
  • Develop infrastructure for model serving, monitoring, logging, and automated evaluation to ensure high reliability and performance of AI services in production.
  • Integrate with multiple LLM providers (e.g., OpenAI, Anthropic, Google) and manage model selection, routing, and fallback strategies for optimal performance and cost.
  • Drive the adoption of best practices in AI privacy, security, and compliance, including data anonymization, secure data handling, and regulatory adherence.
  • Optimize platform performance, scalability, and cost‑efficiency, leveraging cloud‑native technologies and distributed systems.
  • Stay current with advancements in AI infrastructure, MLOps, and LLM applications, and proactively incorporate relevant innovations into ClickUp’s AI platform.
  • Collaborate cross‑functionally with product, frontend, and data teams to deliver seamless, reliable, and user‑centric AI experiences.
Qualifications
  • Extensive experience designing and building scalable AI/ML platforms or infrastructure in a production environment.
  • Proven track record of applying LLMs and AI models to real‑world product features and user‑facing solutions.
  • Deep expertise in backend engineering, distributed systems, and cloud‑native technologies (e.g., Kubernetes, Docker, AWS/GCP/Azure).
  • Proven experience integrating and managing multiple LLMs and AI models, with a strong understanding of their operational requirements and limitations.
  • Proficiency in orchestration frameworks and workflow engines (e.g., LangGraph, Airflow, Kubeflow, Ray, or similar).
  • Strong programming skills in Python, Go, TypeScript or similar languages used for backend and AI platform development.
  • Experience with MLOps best practices, including model deployment, monitoring, logging, and automated evaluation.
  • Demonstrated ability to address AI privacy and security challenges, including data anonymization and compliance with data protection regulations.
  • Familiarity with search technologies and their integration into AI‑driven applications.
  • Excellent collaboration and communication skills, with a track record of working effectively in cross‑functional teams.
  • Passion for staying at the forefront of AI infrastructure and applying new technologies to solve real‑world problems at scale.
Equal Opportunity Employer

ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.

Privacy Notice

ClickUp collects and processes personal data in accordance with applicable data protection laws. You can find further details by viewing our Global Candidate Privacy Notice.

If you are a Philippine Job Applicant, please also see our Philippine Data Privacy Notice for further details.

Visa Sponsorship

Please note we are unable to sponsor or take over sponsorship of an employment visa for roles outside of engineering and product at this time. Sponsorship for engineering and product roles is not guaranteed, but is instead based on the business needs for that specific role at that time. Please reach out to the recruiter with any questions.

Fraud Alert

ClickUp Talent Acquisition will only initiate contact via an @ clickup.com email or through our official careers portal on clickup.com. We will never request fees, payments, or sensitive personal information. Please disregard any offers received outside these channels and report them to support@clickup.com.

AI Processing Notice

ClickUp may use artificial intelligence and machine learning technologies to help review and screen candidates' employment applications against role‑related criteria. These tools support, but do not replace, human decision‑making. If you have questions or need an accommodation in the recruitment process, please contact us at AskPeople@ClickUp.com.

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