Top 11 Big data architect Jobs in Houston, Tx

Principal Data Privacy Architect
Information Technology Senior Management Forum —Spring, TX
- $154,400 - $227,750 a year
- Full-time
- Computer science
- Azure
- Computer Science
- Paid parental leave
- Paid holidays
Principal Data Architect
HP —Spring, TX
- $147,050 - $230,850 a year
- Full-time
- Azure
- Computer Science
- Java
- Paid parental leave
- Paid holidays
Principal Data Architect
Information Technology Senior Management Forum —Spring, TX
- $147,050 - $230,850 a year
- Full-time
- Azure
- Computer Science
- Java
- Paid parental leave
- Paid holidays
Sr. Solution Architect - Endur
Shell —Houston, TX
- $149,000 - $223,000 a year
- Full-time
- Salesforce
- 3 years
- AWS
- Paid parental leave
- Paid holidays
Principal Data Privacy Architect
HP —Spring, TX
- $154,400 - $227,750 a year
- Full-time
- Computer science
- Azure
- Computer Science
- Paid parental leave
- Paid holidays
Solution Architect
Alvarez and Marsal —Houston, TX
- $125,000 - $155,000 a year
- Full-time
- Computer science
- Azure
- Computer Science
- AD&D insurance
- 401(k)
Data Technical Architect
Rysun Labs Inc —Houston, TX
- $70 an hour
- Full-time
- Computer Science
- DevOps
- Master's degree
- Health insurance
- Dental insurance
Quick Apply
Endur Solution Architect
Engineers and Constructors International Inc. —Houston, TX
- Contract
- Salesforce
- 3 years
- AWS
Quick Apply
Sr. Solution Architect - Endur
Shell Energy —Houston, TX
- Full-time
- Salesforce
- 3 years
- AWS
- Paid parental leave
- Paid holidays
Solutions Architect, Manager - Tax Transformation
Deloitte —Houston, TX
- $128,025 - $261,625 a year
- Full-time
- Hybrid work
- Computer science
- Azure
- CPA

Discover related jobs

Based on your search for big data architect jobs.

Snowflake Architect
Tavant Technologies, Inc. —Houston, TX
The ideal candidate has strong data engineering fundamentals, experience with enterprise data platforms, and the ability to work with *ontologies, semantic…
$120,927.67 - $150,719.34 a year
Quick Apply
Snowflake Architect
Biztec global —Houston, TX
They are comfortable working across *Snowflake, AWS, Informatica, dbt, Iceberg, Snowflake Catalog, and Horizon*, and can help connect technical implementation…
$147,067.42 - $177,113.45 a year
Quick Apply
10d

Show more related jobs

Explore jobs in cities nearby

Check out jobs in cities near your current location, Columbus

ServiceNow Principal Domain Architect - Remote
Sentara Hospitals —Columbus, OH
Domain architects create deliverables that help develop target-state guidance (standards, guidelines, individual parts, platforms, and configurations) for…
$106,080.00 - $176,820.80 a year
Quick Apply
AI Architect
Vertiv —Westerville, OH
Strong communication and presentation skills, with the ability to explain complex artificial intelligence concepts and insights to technical and non-technical…

I want to receive the latest job alert for big data architect in houston, tx

By signing in to your account, you agree to SimplyHired's Terms of Service and consent to our Cookie and Privacy Policy.

Explore jobs in more locations

big data architect jobs near houston, tx

Principal Data Privacy Architect

Information Technology Senior Management Forum
Spring, TX

Apply Now

Job Details

Full-time
$154,400 - $227,750 a year

Benefits

Paid parental leave
Paid holidays
Disability insurance
Health insurance
Dental insurance
Flexible spending account
Parental leave
Employee assistance program
Vision insurance
Life insurance

Qualifications

AI models
Zero Trust security
Computer science
Data Integration (Data management)
Azure
Computer Science
Data lake
Cloud security engineering
Automation
ISO standards
Zero trust architecture design
Infrastructure as Code (IaC)
Data Retention (Data management)
Spark
AI tools proficiency
CISSP
Security classification
Generative models
Integration Architecture Design (Architecture design skills)
CCPA
Information Systems
Public Cloud
Scalable systems
Master's degree in cybersecurity
Security compliance frameworks implementation
CCSP
Java
SQL
Information security compliance
GDPR compliance expertise

Full Job Description

Posted Date 7/07/2026

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’s EEO Policy or read about your rights as an applicant under the law here: “Know Your Rights: Workplace Discrimination is Illegal"

Type

Full-time

Apply Now

Refine Your Search

big data architect jobs in houston, tx

Discover related jobs

Explore jobs in cities nearby

I want to receive the latest job alert for big data architect in houston, tx

Explore jobs in more locations

Job Summary

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.

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

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.

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.

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.

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.

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

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.

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.

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.

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.

Effective Communication

Results Orientation

Learning Agility

Digital Fluency

Customer Centricity