Enterprise Security Architect
We are seeking an Enterprise Security Architect to oversee the architecture, design, and implementation of a modern Customer Data Platform (CDP). The ideal candidate will bring deep technical expertise in data engineering, SaaS product development, and AWS-based architectures, coupled with strong leadership skills. This position will define the CDP's technical vision, ensure scalable and secure data solutions, and mentor a team of engineers to deliver best-in-class data management and analytics capabilities.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Compensation & Location
Location: Onsite in Torrance, CA (LA COUNTY)
Pay Range: $74.00 – $81.00 per hour (based on experience and internal equity)
Schedule: Full-time, long-term contract
Work Type: 100% Onsite
Benefits: Health, Vision, Dental, Life Insurance, 401k, Continuing and on-demand education
📍 You must be willing to work onsite in Torrance, CA
✅ Sponsorship is available for this role
‼️ ONLY W2 – NO CORP to CORP – NO 3rd Parties
Position Summary
We are seeking a Enterprise Security Architect to oversee the architecture, design, and implementation of a modern Customer Data Platform (CDP).
The ideal candidate will bring deep technical expertise in data engineering, SaaS product development, and AWS-based architectures, coupled with strong leadership skills.
This position will define the CDP’s technical vision, ensure scalable and secure data solutions, and mentor a team of engineers to deliver best-in-class data management and analytics capabilities.
Key Responsibilities
- Lead the design, development, and deployment of a scalable, secure, and high-performance Customer Data Platform (CDP) SaaS product.
- Architect end-to-end data platforms integrating multiple data sources, APIs, and third-party systems.
- Design modern data architectures including lakehouse frameworks, distributed analytics environments, and scalable data platforms.
- Develop and optimize complex SQL queries for data extraction, transformation, and advanced analytics workloads.
- Build and automate ETL and ELT pipelines using Digdag, Treasure Data, and AWS services.
- Support advanced analytics infrastructure, including data pipelines enabling machine learning and data science workflows.
- Implement data quality controls, monitoring, logging, and alerting across workflows.
- Utilize AWS services such as S3, Lambda, Glue, and Athena to enhance scalability, reliability, and performance.
- Design systems that support both real-time and batch data processing for analytics and operational workloads.
- Ensure compliance with GDPR, CCPA, and enterprise data governance standards.
- Collaborate with cross-functional teams (Data, Product, and Engineering) to translate business requirements into scalable architecture solutions.
- Lead code reviews, promote DevOps best practices, and support CI/CD pipeline implementation.
- Mentor engineers and promote best practices in data engineering, analytics architecture, and platform design.
- Troubleshoot complex data platform and analytics pipeline issues.
- Monitor performance, optimize cost efficiency, and continuously improve platform reliability.
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Required Skills & Experience
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related discipline.
- 15+ years of software development or data engineering experience, including 6+ years in a technical leadership role.
- Proven experience designing and scaling SaaS-based data platforms or customer data environments.
- Strong experience designing analytics-ready data architectures.
- Hands-on expertise with Python, Presto, and Hive.
- Expert-level SQL skills for complex queries, data modeling, and performance optimization.
- Deep understanding of ETL/ELT pipelines, data orchestration, and workflow automation.
- Experience working with AWS data services (S3, Glue, Athena, Lambda).
- Familiarity with Treasure Data and Digdag is a strong plus.
- Strong knowledge of data governance, privacy, and compliance frameworks (GDPR, CCPA).
- Experience integrating Customer Data Platforms (CDPs) with CRM or marketing technology ecosystems.
- Strong communication skills with experience working in Agile engineering environments.
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Desired / Preferred Experience
Candidates with exposure to the following modern data and analytics architectures will be strongly preferred:
- Lakehouse architecture design
- Data mesh or distributed data ownership environments
- Advanced analytics platform architecture
- Machine learning pipeline infrastructure
- Experience working with large-scale data platforms or enterprise analytics ecosystems
- Prior experience in Big 4 consulting or large enterprise environments
- Familiarity with DevOps practices and CI/CD pipelines
- Experience optimizing workflow orchestration for large-scale data systems
- Background supporting data science, analytics, or AI-driven personalization platforms
- Stable career progression with demonstrated technical leadership and mentorship
- ✅ We are particularly interested in candidates who have designed data platforms that support both operational data management and advanced analytics use cases.
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