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Cybersecurity Data Engineer Jobs in Austin, TX (NOW HIRING)

The architect will partner closely with Data Engineering, Cybersecurity, Legal, Privacy, AI Governance, Product, and Enterprise Architecture teams to ensure customer, employee, partner, and sensitive ...

Cybersecurity Engineer Location: Remote Security Clearance: Active DoD Secret Clearance We question ... Data Protection * Hands on Experience with Secretes Management * Experience in auditing and ...

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

They are seeking a talented and driven Data Engineer to help elevate their data platform by ... Preferred : • Experience in fintech, cybersecurity, or fraud prevention. • Familiarity with ...

GCP Data Engineer

Austin, TX

$113K - $136K/yr

Stay up to date with emerging trends and technologies in cloud-based data engineering and cyber security. * Exceptional communication skills, including the ability to gather relevant data and ...

GCP Data Engineer

Austin, TX

$113K - $136K/yr

Stay up to date with emerging trends and technologies in cloud-based data engineering and cyber security. * Exceptional communication skills, including the ability to gather relevant data and ...

Position Summary As a Cybersecurity Engineer, you will be responsible for implementing, and ... This helps prevent malware infections, ransomware, unauthorized data transfer, and other threats ...

The Cybersecurity Engineer - Cloud is responsible for designing, implementing, and operating ... Application & Data ProtectionStrong understanding of: API security (OAuth/OIDC, tokenbased auth ...

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Showing results 1-20

Cybersecurity Data Engineer information

See Austin, TX salary details

$44.1K

$128.6K

$175.9K

How much do cybersecurity data engineer jobs pay per year?

As of Jul 16, 2026, the average yearly pay for cybersecurity data engineer in Austin, TX is $128,576.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $136,300.00 per year, depending on experience, location, and employer.

What does a Cybersecurity Data Engineer do?

A Cybersecurity Data Engineer is responsible for designing, building, and maintaining systems that collect, process, and analyze security-related data. Their main goal is to help organizations detect and respond to cyber threats by ensuring that data pipelines and storage solutions are secure and efficient. They often work with large datasets, security tools, and machine learning algorithms to identify vulnerabilities and unusual activity. Additionally, they collaborate with other IT and security professionals to implement best practices and enhance overall cybersecurity posture.

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

To thrive as a Cybersecurity Data Engineer, you need strong skills in data engineering, cybersecurity best practices, and programming languages such as Python or SQL, typically supported by a degree in computer science or a related field. Familiarity with security information and event management (SIEM) systems, big data tools like Hadoop or Spark, and certifications such as CISSP or CEH are highly valuable. Analytical thinking, problem-solving abilities, and effective communication set standout professionals apart in this role. These skills are crucial for designing secure data pipelines, detecting threats, and ensuring organizational data integrity.

What is the difference between Cybersecurity Data Engineer vs Cybersecurity Analyst?

AspectCybersecurity Data EngineerCybersecurity Analyst
Required CertificationsCompTIA Security+, CISSP, CEHCompTIA Security+, CISSP, CEH
Work EnvironmentData-focused, engineering teams, IT departmentsSecurity operations centers, incident response teams
Employer & Industry UsageTech companies, finance, healthcareGovernment agencies, corporations, cybersecurity firms
Common Search & ComparisonYesYes

While both roles require cybersecurity certifications and work within security-focused environments, Cybersecurity Data Engineers primarily develop and manage data infrastructure for security analytics, whereas Cybersecurity Analysts focus on monitoring, threat detection, and incident response. Understanding these differences helps organizations assign the right skills to their security teams.

How does a Cybersecurity Data Engineer typically collaborate with security analysts and IT teams?

Cybersecurity Data Engineers work closely with security analysts and IT teams to design, implement, and maintain data pipelines that support threat detection and incident response. They collaborate by integrating various data sources, ensuring data quality, and providing timely access to relevant information for analysis. Frequent communication and regular meetings are common to align on project requirements, prioritize tasks, and troubleshoot issues together. This collaborative approach ensures that security teams have the accurate, actionable data they need to protect organizational assets effectively.
What are popular job titles related to Cybersecurity Data Engineer jobs in Austin, TX? For Cybersecurity Data Engineer jobs in Austin, TX, the most frequently searched job titles are:
What cities near Austin, TX are hiring for Cybersecurity Data Engineer jobs? Cities near Austin, TX with the most Cybersecurity Data Engineer job openings:
Principal Data Privacy Architect

Principal Data Privacy Architect

Hp

Austin, TX

Full-time

Medical, Dental, Vision, Life, PTO

Posted 9 days ago


HP rating

7.7

Company rating: 7.7 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

61st of 142 rated electronics manufacturers


Job description

Principal Data Privacy Architect

Description -

Job Summary- Role Purpose
  • This role will design and implement scalable, AI-ready data privacy architecture across enterprise data environments, applications, and AI-enabled workflows.
  • The Principal Data Privacy Architect will serve as a hands-on subject matter expert responsible for embedding privacy-by-design, consent enforcement, data sovereignty, data loss prevention, and compliance controls into large, complex global data environments.
  • The architect will partner closely with Data Engineering, Cybersecurity, Legal, Privacy, AI Governance, Product, and Enterprise Architecture teams to ensure customer, employee, partner, and sensitive enterprise data is accessed, processed, shared, retained, and protected in a compliant, secure, and trustworthy manner.
- Why This Role Matters
  • Architect for Trust & Scale: Build reusable privacy architecture patterns that enable secure, compliant, and scalable data usage across platforms, products, and regions.
  • Enable Responsible AI: Design privacy guardrails for AI agents, generative AI, RAG pipelines, model inputs and outputs, embeddings, vector stores, and automated data workflows.
  • Reduce Risk While Enabling Innovation: Translate privacy, consent, regulatory, and data sovereignty obligations into practical engineering controls that accelerate business outcomes.
Responsibilities- Think Customer First
  • Embed customer trust, transparency, and privacy-by-design principles into enterprise data platforms and customer-facing applications.
  • Design consent-aware data access and usage patterns across analytics, personalization, marketing, product telemetry, support, and AI use cases.
  • Ensure customer data is collected, processed, shared, retained, and deleted according to approved purposes, consent preferences, and regulatory obligations.
- Innovate for Growth
  • Architect reusable privacy engineering components, including APIs, SDKs, reference architectures, automation patterns, and policy-as-code controls.
  • Design privacy controls for AI agents and AI-enabled workflows that access, process, summarize, or publish sensitive data.
  • Build technical patterns for data minimization, anonymization, pseudonymization, tokenization, encryption, masking, and secure data sharing.
- Act with Integrity
  • Partner with Legal, Privacy, Cybersecurity, and Compliance teams to translate global privacy regulations and internal policies into enforceable technical controls.
  • Support compliance with GDPR, CCPA/CPRA, LGPD, PIPL, India DPDP Act, data sovereignty mandates, cross-border transfer requirements, and regional data residency obligations.
  • Define auditable controls for consent enforcement, access monitoring, retention, deletion, lineage, and compliance evidence collection.
- Build for the Future
  • Establish privacy architecture patterns across data warehouses, lakehouses, metadata platforms, customer data platforms, AI/ML environments, vector databases, and cloud platforms.
  • Integrate sensitive data discovery, classification, lineage, DLP, DSPM, IAM, KMS, and monitoring capabilities into the enterprise data ecosystem.
  • Advance automated compliance monitoring, privacy control validation, and risk detection across the data lifecycle.
- Work as One Team
  • Collaborate with Data Engineering, Product, AI Governance, Cybersecurity, Legal, Privacy, and Enterprise Architecture teams to embed privacy controls into delivery workflows.
  • Provide hands-on architecture guidance for high-risk data initiatives, AI programs, customer data products, and platform modernization efforts.
  • Mentor engineers, architects, data scientists, and product teams on privacy engineering best practices.
Strategic & Technical Focus Areas
  • AI-Ready Privacy Architecture: Privacy controls for AI agents, generative AI, RAG pipelines, model inputs and outputs, embeddings, vector stores, and automated data workflows.
  • Consent & Purpose-Based Usage: Consent propagation, purpose limitation, consent revocation, customer preference enforcement, and downstream data usage controls.
  • Data Loss Prevention & Sensitive Data Protection: DLP integration, sensitive data classification, risky sharing detection, exfiltration prevention, and AI prompt/output inspection.
  • Data Sovereignty & Compliance Engineering: Regional data residency, cross-border transfer controls, localization requirements, encryption key residency, and audit evidence automation.
  • Reusable Privacy Frameworks: Standardized architecture patterns for encryption, masking, tokenization, anonymization, retention, deletion, access control, and monitoring.
Education & Experience & Skills- Education & Experience
  • Bachelor's or master's degree in Computer Science, Engineering, Information Systems, Cybersecurity, Data Engineering, or related field.
  • 10+ years of progressive experience in data privacy, data protection, cybersecurity, data architecture, or enterprise data platforms.
  • Proven experience architecting privacy and data protection solutions in large, complex, global environments.
  • Hands-on experience implementing privacy-by-design, consent management, data sovereignty, DLP, and sensitive data protection controls.
- Technical Expertise
  • Strong understanding of global privacy regulations and frameworks, including GDPR, CCPA/CPRA, LGPD, PIPL, India DPDP Act, NIST, ISO 27001, and related privacy/security standards.
  • Experience with cloud platforms such as AWS, Azure, or GCP, and enterprise data platforms including data warehouses, lakehouses, data catalogs, metadata platforms, and big data environments.
  • Working knowledge of privacy and data protection technologies such as BigID, OneTrust, Securiti, Collibra, Informatica, Microsoft Purview, AWS Macie, Google Cloud DLP, Azure Information Protection, DLP, DSPM, CASB, IAM, and KMS capabilities.
  • Strong technical skills in Python, Java, SQL, APIs, Spark, data pipelines, infrastructure-as-code, and policy-as-code.
  • Experience with AI/ML, generative AI, AI agents, RAG architectures, vector databases, feature stores, model governance, or AI-enabled data products.
- Leadership & Business Skills
  • Ability to translate legal, privacy, compliance, and business requirements into scalable technical architecture.
  • Strong communication and influencing skills with engineers, architects, legal teams, privacy teams, product leaders, and senior executives.
  • Demonstrated ability to balance customer trust, regulatory compliance, engineering practicality, and business agility.
- Preferred Qualifications
  • Certifications such as CIPP/E, CIPP/US, CIPM, CIPT, CISSP, CCSP, CDPSE, or equivalent.
  • Experience building consent management platforms, privacy preference centers, data subject rights automation, or customer data governance capabilities.
  • Experience implementing purpose-based access control, attribute-based access control, zero-trust data architecture, or data-centric security models.
  • Active industry participation, publications, or memberships related to privacy engineering, AI governance, cybersecurity, or customer trust.
- Cross-Org Skills
  • Effective Communication
  • Results Orientation
  • Learning Agility
  • Digital Fluency
  • Customer Centricity

Salary

The pay range for this role is 154,400.00 - 227,750.00 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United
States of America candidates only). Pay varies by work location, job-related
knowledge, skills, and experience.

Benefits:

HP offers a comprehensive benefits package for this position, including:

* Health insurance
* Dental insurance
* Vision insurance
* Long term/short term disability insurance
* Employee assistance program
* Flexible spending account
* Life insurance
* Generous time off policies, including;
* 4-12 weeks fully paid parental leave based on tenure
* 11 paid holidays
* Additional flexible paid vacation and sick leave (US benefits overview
[https://hpbenefits.ce.alight.com/])


The compensation and benefits information is accurate as of the date of this
posting. The Company reserves the right to modify this information at any time,
with or without notice, subject to applicable law.

Job -

Data & Information Technology

Schedule -

Full time

Shift -

No shift premium (United States of America)

Travel -

Relocation -

Equal Opportunity Employer (EEO) -

HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).

Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.

For more information, review HP'sEEO Policy or read about your rights as an applicant under the law here: "Know Your Rights: Workplace Discrimination is Illegal"


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About HP

Sourced by ZipRecruiter

HP is a technology company that operates in more than 170 countries around the world united in creating technology that makes life better for everyone, everywhere. From the boardroom to factory floor, we create a culture where everyone is respected and where people can be themselves, while being a part of something bigger than themselves. We celebrate the notion that you can belong at HP and bring your authentic self to work each and every day. When you do that, you're more innovative and that helps grow our bottom line. Our history: HP's commitment to diversity, equity and inclusion - it's just who we are. From the boardroom to factory floor, we create a culture where everyone is respected and where people can be themselves, while being a part of something bigger than themselves. We celebrate the notion that you can belong at HP and bring your authentic self to work each and every day. When you do that, you're more innovative and that helps grow our bottom line.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Palo Alto, CA, US

Year founded

1939