Description:

Lead the definition and evolution of the enterprise data platform strategy, aligning architecture standards with business priorities and analytical requirements.
Develop and maintain enterprise architecture artifacts, ensuring accuracy and accessibility within the architecture repository.
Evaluate and govern the selection of data platforms and ETL/ELT tools, balancing scalability, performance, security, and cost.
Provide technical leadership to data engineering and analytics teams, translating architecture standards into implementable solutions.
Define architectural guardrails for scalability, performance, and disaster recovery.
Establish standards for platform operations, reliability, and lifecycle management.
Ensure data platform architectures incorporate security controls and regulatory compliance.
Standardize ETL/ELT and data integration patterns for analytics and reporting.
Participate in governance forums, providing architectural guidance for data initiatives.
Assess emerging technologies and drive innovation in AI-powered data workflows.

Requirements:

Bachelor’s degree in IT, Data Science, Computer Science, or related field; or equivalent experience.
7+ years in database engineering with 3+ years in database architecture design.
Experience architecting enterprise data platforms across cloud environments (Azure, Google Cloud).
Deep knowledge of Snowflake as an enterprise data warehouse platform.
Hands-on familiarity with modern data platforms (e.g., Azure Data Lake, Databricks).
Strong technical fluency with SQL and Python for data pipeline implementation.
Ability to design analytics-ready datasets and integrate data sources securely.
Familiarity with infrastructure-as-code, automation, and CI/CD for data platforms.

Skills