Principal Cloud Data Architect

Join our Digital Identity & Fraud Engineering team as a Principal Cloud Data Architect. In this role, you will be responsible for the technical direction of our products, ensuring the use of appropriate technologies and driving initiatives that bring customer value and operational efficiency. You will work closely with enterprise teams to align technical choices with the overall architecture of our products, mentor team members, and collaborate with data engineers to prepare and deliver raw data for modeling. Additionally, you will assess and advocate for data management technologies and practices, interpret and deliver strategic plans, and drive innovative technology solutions.

• Designing secure, scalable, and cost-effective data architecture, and leading the adoption and integration of AWS/Azure architecture services.
• Mentoring team members and collaborating with enterprise teams to ensure technical choices align with the overall architecture of products.
• Driving innovative technology solutions through thought leadership on emerging trends, and advocating for data management technologies and practices.
• Familiarity with recommending data governance standard methodologies including MDM, security, privacy and policies
• Advanced proficiency in end-to-end data architecture solutions including ingestion, storage and relational modeling using industry standard languages including SQL and Python
• Demonstrated proficiency in the design and implementation of modern data architectures and concepts such as cloud services (e.g., AWS, Azure, GCP), real-time data distribution (e.g., Kafka, Kinesis, DataFlow, Airflow), NoSQL (e.g., MongoDB, DynamoDB, HBase, CosmosDB), GraphQL and modern data warehouse tools including Snowflake and DataBricks
• Ability to think strategically and relate architectural decisions and recommendations to customer needs
• 12+ years of Proven ability implementing with a variety of on-premises and cloud data management, integration, visualization, and analytical technologies
• Ability to assess traditional and modern data architectural components based on business needs