Senior Data Security & Databricks Architect

STRAVEXA; Seattle (WA); Hybrid; USD 180,000 - 240,000; Full time

Job summary

STAFFXPERT LLC in Seattle, WA is seeking a Senior Data Security & Databricks Architect to lead secure, scalable data platform design within the Databricks Lakehouse ecosystem.

The role requires expertise in data governance, encryption, RBAC, and cloud architectures across Azure; you will collaborate with security, governance, and analytics teams to enable governed data access and compliant analytics across the enterprise.

Qualifications

• Bachelor's degree and 10+ years in data engineering, architecture or security.
• Experience designing secure data platforms and enterprise data governance.
• Hands-on Databricks expertise with secure data access and lineage.

Responsibilities

• Architect secure, scalable data platforms within the Databricks Lakehouse ecosystem.
• Enforce data governance, security, and compliance frameworks across the org.
• Implement data masking, encryption, and access controls for sensitive data.
• Design RBAC policies and data access governance across cloud environments.
• Build and optimize data pipelines, APIs, and analytics solutions.
• Collaborate with security, governance, and engineering teams to set standards.

Skills

Databricks Lakehouse Platform

Data governance

Data security

Cloud architecture (Azure)

Python

SQL / Spark / PySpark

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field

Tools

Delta Lake

Apache Iceberg

Snowflake integration

RBAC tooling

Job description

Senior Data Security & Databricks Architect

Location: Seattle, WA (Hybrid)

Job Summary

STAFFXPERT LLC is seeking a Senior Data Security & Databricks Architect on behalf of our client in Seattle, WA. This role is ideal for a seasoned data professional with deep expertise in Databricks, data governance, cloud architecture, and enterprise security. The successful candidate will lead the design and implementation of secure, scalable, and compliant data solutions while enabling advanced analytics and AI-driven data access across the organization.

Key Responsibilities

• Architect and implement secure, scalable data platforms within the Databricks Lakehouse ecosystem.


• Design and enforce enterprise data governance, security, and compliance frameworks.


• Develop strategies for protecting sensitive data through data classification, masking, encryption, and access controls.


• Implement and manage Role-Based Access Control (RBAC) and data access governance policies.


• Build and optimize high-performance data pipelines, applications, and analytics solutions.


• Design interoperable data architectures utilizing Delta Lake, Apache Iceberg, and modern data platform technologies.


• Integrate Databricks with cloud-based data platforms and enterprise data ecosystems.


• Create dashboards, monitoring frameworks, and operational reporting solutions.


• Support AI/ML initiatives by enabling governed, secure, and self-service data access.


• Optimize platform performance through query tuning, caching strategies, and workload management.


• Collaborate with engineering, security, governance, and business stakeholders to establish best practices and architecture standards.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.


• 10+ years of experience in Data Engineering, Data Architecture, Data Security, or related disciplines.


• Strong hands-on experience with the Databricks Lakehouse Platform.


• Proven expertise in data governance, data security, and sensitive data management, including PHI/PII protection.


• Experience implementing data masking, encryption, data classification, and access control strategies.


• Strong knowledge of Delta Lake, Apache Iceberg, and modern data lakehouse architectures.


• Experience working with cloud platforms, preferably Microsoft Azure.


• Experience integrating Databricks with Snowflake or similar enterprise data platforms.


• Proficiency in Python, SQL, Spark, and PySpark/Scala.


• Experience building scalable data applications, APIs, and enterprise data solutions.


• Strong understanding of performance optimization, query tuning, and platform scalability.


• Excellent communication, analytical, and stakeholder management skills.

Preferred Qualifications

• Exposure to AI/ML platforms and secure analytics environments.


• Experience within regulated industries such as healthcare, life sciences, or financial services.


• Databricks, Azure, Cloud, or Security-related certifications.


• Knowledge of enterprise metadata management and data governance tools.