Principal Data Architect

Responsibilities

• Define multi-tenant enterprise data architecture for the platforms
• Lead data architecture practice and represent Data Engineering at the enterprise level
• Technical subject matter expert in the data ecosystem, including AWS/Snowflake, providing input into architecture, platforms, and development strategies and methodologies – includes mentorship of engineering and platform teams via design reviews, code reviews, etc.
• Define data engineering and data platform integration framework and standards
• Mentor, coach and build learning program to efficiently and quickly onboard new people in the team and ensure standards are understood and followed
• Facilitate cross-team collaboration for defining and building enterprise data management architecture from principles to tools, oversee cross-functional adoption of the new architecture, and enable a new level of engineering efficiency when working with data
• Lead the strategy and implementation for migration from the existing data warehouse platforms onto the new Enterprise Data Platform (EDP) on AWS/Snowflake
• Lead the shift towards DevSecOps processes for the Data & Analytics delivery functions, emphasizing continuous integration, release management, and automated testing to maximize development agility and improve time to market
• Interface with key business functions (i.e., Compliance, Actuarial, Marketing, Operations, Clinical, etc.) and IT Analysis teams to assess business functional requirements and translate them into data and integration requirements
• Guide onsite/onshore/offshore technical resources from consulting partners, communicate architecture standards and best practices, establish a high impact development process, drive excellence in all deliverables
• Establish daily cadence with project team to prioritize and execute work items through adoption of Agile principles and processes
• Manage relationships with external vendors to determine technical competence and identify integration opportunities
• Be a hands-on practitioner for end-to-toe delivery of AWS/Snowflake platforms, capabilities, and content

Qualifications

• Ability to understand, drive, and deliver technology solutions in AWS and Snowflake
• Demonstrated understanding of Data architecture and components, especially for Data Warehousing, including Snowflake, dbt Data transformations, Airflow, Data Cataloging tools like Alation; other key integration platforms like Boomi/Fivetran, BI tools like Tableau/Power BI/Sigma, and AI/ML tools like Dataiku/Cortex/Snowflake Intelligence
• Demonstrated understanding of and experience with modern Data Warehouse concepts, including Data Lake/Data Warehouse/Data Mart implementations, SQL-based transformations, and ELT methodology
• Understanding of Data Mesh principles, treating data as product, emphasizing domain specific data ownership and governance
• Solid understanding of DevSecOps and Agile methodology, comfortable with Jira and AWS DevOps and GitLab
• Ability to lead project and technical teams and deliver solutions
• Ability to partner with Data Solution Architects in building APIs and other integrations required
• Ability to provide mentorship to Snowflake administrators in support of role/policy administration, replication, zero-copy clone etc.
• Ability to provide technical leadership to Snowflake-related project and support teams
• Demonstrated planning, coordination, and execution skills
• Ability to conduct POCs, and demonstrable work products when adapting new features
• Ability to successfully collaborate with business partners
• Knowledgeable and skilled in Snowflake-related technologies, including platforms and tools for meeting business use cases for all forms of analytics and AI/ML functionality
• Strong knowledge of ELT, ETL, CDC, API, messaging, streaming, and all forms of data ingestion techniques applicable to cloud-based Data & Analytics
• Strong skills in SQL
• Ability to build data pipelines as part of integrations design
• No-SQL; relational & non-relational platforms; multiple file formats, including Parquet, AVRO, JSON, XML, CSV, etc.