Description

You will own the end-to-end data architecture for the Risk Management Back Office.

Responsibilities

• Design and maintain scalable data architectures on AWS and Snowflake to support trade settlement, collateral management, and regulatory reporting.
• Develop conceptual, logical, and physical data models for risk data domains.
• Lead the development of high-performance data ingestion and transformation pipelines using Python and AWS services.
• Establish data governance frameworks, defining standards for lineage, metadata management, and data quality.
• Architect data marts and semantic layers optimized for analytics using Sigma and Power BI.
• Implement data security solutions for classification, access control, and regulatory compliance.
• Provide technical mentorship to data engineers and analysts while driving best practices in cloud infrastructure.

Required Skills

• 15+ years of experience in data architecture or data engineering delivering large-scale solutions.
• Extensive hands-on experience with Snowflake, including performance tuning and cost management.
• Expert-level knowledge of the AWS ecosystem, specifically S3, EC2, Lambda, Glue, and IAM.
• Advanced Python proficiency for data manipulation and pipeline automation.
• Deep domain knowledge of financial services back-office operations and Risk Management.
• Expert understanding of data architecture patterns including Data Warehousing, Data Lake, and Data Mesh.
• Proven experience architecting data solutions for BI tools such as Sigma or Power BI.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.

Preferred Skills

• Experience with data transformation tools like dbt and infrastructure-as-code using Terraform or CloudFormation.
• Knowledge of streaming technologies like Kafka or Kinesis and financial instruments including equities, fixed income, and derivatives.

Key Skills

Education

Any Graduate