Cloud Data Architect, Exiger

• 5+ years of experience in data architecture, warehousing, or administration
• 3+ years of hands-on experience with Snowflake, including performance tuning, cost optimization, and security
• Strong experience with query engines such as Trino, Athena, or Presto, and metadata catalogs such as Polaris or AWS Glue Catalog
• Experience designing and maintaining data lakes and open table formats (e.g., Iceberg, Delta, or Hudi)
• Expertise in AWS data services — particularly S3, Glue, IAM, Lambda, SQS, SNS, and Secrets Manager
• Strong understanding of data modeling, schema design, and ELT/ETL best practices
• Hands-on experience with Python or Java for automation and data pipeline development
• Experience with streaming data ingestion (Kafka, Kinesis, or equivalent)
• Strong communication and collaboration skills to work across data engineering, DevOps, and analytics teams
• Experience with Terraform, CI/CD pipelines, and modern data orchestration tools (e.g., Airbyte, Matillion, or Airflow)

Desirable

• We are seeking a Cloud Data Architect / Administrator to design, evolve, and maintain the data platforms that power our analytics and risk intelligence products
• This role blends traditional data administration with modern data architecture — focusing not only on managing data systems, but also on shaping how data is modeled, governed, and integrated across our platforms
• Architect the evolution of our data ecosystem, helping to design and implement a medallion architecture (bronze/silver/gold layers) to support scalable, traceable data movement and quality monitoring
• Plan and coordinate data cadences, ensuring that data ingestion and transformation processes are efficiently synchronized across layers
• Lead the transition toward a hybrid data architecture based on AWS S3, Apache Iceberg, Polaris, and Trino (or similar query engine) — while maintaining and optimizing our existing Snowflake environment during the transition
• Design and govern data models that support both analytical and operational workloads, balancing cost, performance, and scalability
• Collaborate with developers and analysts to define end-to-end data integration processes using ETL/ELT frameworks for structured, semi-structured, and unstructured data
• Administer and optimize Snowflake environments — including warehouse sizing, data clustering, cost optimization, and user access management — while planning for gradual migration of workloads to open table formats and object storage
• Develop and maintain data infrastructure as code using Terraform and CI/CD pipelines to automate deployment, configuration and management of data resources
• Evaluate and implement data cataloging, governance, and lineage tools, with an emphasis on Polaris for metadata and discovery
• Perform ongoing analysis of data storage and query performance to improve efficiency, cost, and maintainability