Associate Technical Architect

Job Description:

                                                          ANZ Media Reporting

Role Overview

As a Snowflake Principal Data Engineer, you will lead the design and delivery of enterprise-grade data platforms that enable advanced analytics and marketing performance insights. This role demands deep technical expertise in Snowflake architecture, cloud infrastructure automation, and data engineering best practices.

Key Responsibilities

• Architect and implement Snowflake solutions, including schema design, role-based access control, security policies, and workload optimization for large-scale, high-performance environments.
• Define and enforce data governance frameworks, ensuring compliance, lineage, and data quality across all assets.
• Design and oversee Data Vault 2.0 implementations for scalable, auditable, and flexible data warehousing.
• Build and optimize data ingestion pipelines integrating APIs from adtech/martech platforms (e.g., DV360, The Trade Desk, SA360) into Snowflake.
• Leverage AWS services (S3, Glue, Lambda, IAM) for cloud-native data processing and storage.
• Use Terraform to automate infrastructure provisioning and manage AWS resources following Infrastructure-as-Code principles.
• Collaborate with business and technical stakeholders to translate requirements into robust, secure, and cost-efficient data architectures.
• Establish performance tuning strategies for Snowflake, including query optimization, clustering, and resource monitoring.
• Drive adoption of engineering best practices, CI/CD workflows, and automation across data teams.
• Act as the technical authority on Snowflake architecture, security, and integration patterns.

Required Skills & Experience

• 10+ years in data engineering or architecture, with 3+ years focused on Snowflake solution design.
• Expert-level knowledge of Snowflake architecture, including schema design, role-based security, workload management, and automation.
• Proven experience implementing Data Vault 2.0 methodologies.
• Strong proficiency in SQL and Python for data modeling and automation.
• Hands-on experience with AWS services (S3, Glue, Lambda, IAM) and cloud-native data solutions.
• Advanced skills in Terraform for infrastructure automation and resource orchestration.
• Familiarity with data orchestration tools (e.g., Airflow) and CI/CD pipelines.

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