Data Architect(Azure)

They MUST be onsite 3 days a week in Allentown, PA Louisville KY, or Providence, RI.

175597 Submission format please complete in full:

First Middle Last Name

Pay Rate:

Skill Highlights- please indicate the # of years on each of the following skills:

• Data Architecture
• Azure
• Purview
• Snowflake
• Defender
• Experience with utilities or highly regulated industries.
• Structured data protection in data lakes
• Azure Synapse
• Experience contributing to LLM security or responsible AI design patterns.
• SANS/GIAC, CISSP, or Azure Security certification.
• Experience with legacy data cleanup initiatives, e.g., tape archive migration.
• Experience with DSPM platform.

Visa Status:

Location:

Availability to interview:

Availability to start:

LinkedIn Profile:

Phone Number:

Email Address:

Last 4 of SSN:

MM/DD of birth:

Job Description:

Callouts:
-This is a hybrid position requiring on-site presence three days per week at one of our local offices, located in Allentown, PA (Lehigh Valley), Louisville, KY, or Providence, RI.
- Looking for experience with Snowflake, Microsoft Defender, DLP tools, Azure Purview and with a data engineering background that is operating in an oversight role or assisting a larger organization using those tools.

The client is seeking a highly skilled Data Security Principal Architect to join our Cybersecurity organization. The Data Security Principal Architect will serve as a strategic leader and technical expert, responsible for defining and implementing robust data protection frameworks across our digital estate. This hybrid role bridges traditional Microsoft Information Protection and compliance tools with modern AI-centric data security practices, including encryption for LLM pipelines, secure vector stores, and legacy data remediation. This individual will collaborate closely with Security Engineering, Data Governance, Cloud Ops, and AI/ML teams to secure data throughout its lifecycle.
Responsibilities

ESSENTIAL FUNCTIONS:
Define and own the data protection strategy across structured, semi-structured, and unstructured data. Align with regulatory, legal, and business mandates (e.g., NERC, SOX, CCPA, GDPR).
Architect and deploy Azure Purview for data classification, and insider risk management policies.
Lead secure implementation of AI Data Pipelines (RAG, Vector DBs), TDE for SQL workloads, and explore applicability of Fully Homomorphic Encryption (FHE) and Differential Privacy (DP) for AI/LLM pipelines.
Develop strategies for legacy data de-duplication, archiving, and migration. Evaluate long-term retention risk and optimize lifecycle policies.
Implement and manage DLP rules across email, endpoints, cloud storage, and collaboration platforms (e.g., Microsoft 365, SharePoint).
Provide architectural guidance to product teams and AI/ML engineers. Author security patterns, threat models, and playbooks.
Evaluate and integrate third-party tools for data discovery, monitoring, and tokenization. Drive automation around classification and response.
Define DSPM Strategy and Architecture.
Define Data Incident Protocol and Playbook.
Performs other duties as assigned.
Complies with all policies and standards.
Qualifications
REQUIRED EDUCATION:
Bachelor's Degree in Computer Science, Information Security, and/or a related field or an equivalent level of experience on a year on year basis.
REQUIRED EXPERIENCE:

10+ years in information security or date architecture roles.

PREFERRED QUALIFICATIONS:
Previous experience with utilities or highly regulated industries.
Working knowledge of structured data protection in data lakes or Azure Synapse.
Experience contributing to LLM security or responsible AI design patterns.
SANS/GIAC, CISSP, or Azure Security certification.
Experience with legacy data cleanup initiatives, e.g., tape archive migration.
Experience with DSPM platform.
Strong understanding of cryptographic primitives and modern data security standards (AES, SHA, TLS, etc.) as well as an understanding of proposed quantum ready cryptography standards.
Excellent communication skills and the ability to influence technical and executive stakeholders.
Demonstrated ability to assess risk trade-offs between security, usability, and operational efficiency.
Deep interest in AI safety, responsible data stewardship, and future-proofing sensitive workloads.