Snowflake Data Governance & Security

The Snowflake Data Governance
SME will lead the design and implementation of the Pacific Data Platform, with
primary responsibility for ensuring the Pacific data platform is
compliant with data governance best practices. The role requires strong hands-on experience securing enterprise data
while supporting scalable analytics, reporting, and application requirements.

Key
Responsibilities

Define and implement Data Governance standards covering data ownership,
classification, lineage, quality, and compliance.

Design and maintain Row Access Policies (RAP) to control data visibility by
region, market, business unit, and user entitlement.

Implement Role-Based Access Control (RBAC), role hierarchies, least-privilege
access, and database-level permissions.

Protect sensitive data through dynamic data masking, tag-based policies, and column-level security.
Establish access reviews, audit monitoring, and secure authentication and
integration practices.

Design scalable data models and guide data integration, SQL optimization, and
Snowflake performance tuning.

Automate deployment of security policies and database changes using Git, Azure DevOps, and CI/CD.
Collaborate with business, security, governance, and engineering teams
to enforce architecture standards.

Key Qualifications
Experience: 8+
years of overall experience in data architecture, data engineering, or
enterprise data platforms, with substantial hands-on Snowflake experience.
Proven ability to lead solution design, data modelling, integration, and
implementation of scalable enterprise platforms.

Data
Governance and Snowflake Security: Strong hands-on expertise in defining governance frameworks covering
data ownership, stewardship, classification, metadata, lineage, and data
quality. Proven experience implementing Row Access Policies (RAP), Role-Based
Access Control (RBAC), role hierarchies, least-privilege permissions, dynamic
data masking, and tag-based masking. Ability to enforce access at database,
schema, object, row, and column levels.

Streamlit
and Snowflake Cortex: Experience developing interactive Streamlit applications for analytics
and conversational data access. Hands-on knowledge of Cortex Analyst and
semantic modelling for natural-language queries, Cortex Search for information
retrieval, and Cortex Agents for orchestrating analytical and search capabilities.
Ability to evaluate response accuracy and implement appropriate access controls for
AI applications.

SQL,
Python, and Performance Optimization: Advanced SQL skills
covering complex queries, stored procedures, incremental processing, and query
tuning. Strong Python experience for data processing, API integration, and
automation. Ability to analyze query profiles, optimize warehouse usage, and
balance performance with cost.
Governance
Controls and Compliance: Experience protecting sensitive and personally identifiable information
through classification, masking, and controlled access. Ability to conduct
access reviews, monitor user activity, maintain audit evidence, and implement
controls aligned with organizational privacy, retention, and compliance
requirements.

Data
Integration: Experience building reliable ingestion and transformation pipelines
using Python, Azure Data Factory, AWS Glue, or equivalent tools. Strong
understanding of full loads, incremental loads, Change Data Capture (CDC), data
validation, error handling, and pipeline monitoring.

Cloud
and DevOps: Familiarity with AWS services such as S3 and IAM, including secure
integration with Snowflake. Experience with Git, Azure DevOps, and CI/CD
pipelines to version, review, test, and deploy database objects, security
policies, and application changes across environments.

Education: Bachelor’s
or master’s degree in computer science, Information Technology, Engineering, or
a related field. Relevant Snowflake, cloud, or data architecture certifications
are preferred.

Personal
Strengths

Communication: Ability
to explain architecture, governance, security, and AI concepts clearly to
technical teams and business stakeholders.

Stakeholder
Management: Ability to collaborate with data owners, security teams, application
teams, and business leaders to align requirements and resolve priorities.

Architectural
Leadership: Ability to define standards, evaluate design decisions, mentor
engineers, and guide teams toward secure and maintainable solutions.

Delivery
Management: Ability to manage multiple initiatives, dependencies, and timelines
across distributed teams.

Problem-Solving: Strong
analytical judgment, with the ability to clarify ambiguous requirements,
identify risks, and recommend practical solutions.