Description

Design and implement enterprise data warehouse solutions and next-generation financial data models. Own the release pipeline for large-scale data infrastructure.

Responsibilities

• Develop frameworks to load and transform gigabytes of historical data into Data Vault modeling designs.
• Design financial data models capable of handling both EOD and real-time streaming data.
• Build and optimize big data pipelines and architectures for heavy read efficiency and data quality.
• Lead the design of next-generation data warehouse solutions using cloud technologies and industry standards.

Required Skills

• 10+ years building large-scale data warehouse solutions within a total 15-year IT career.
• 8+ years of experience within the investment banking domain.
• Expertise in Spark (Python/Scala) and Databricks batch and streaming solutions, including Delta Lake and Lakehouse.
• Hands-on experience with Microsoft Azure, Azure Data Factory, Cosmos DB, and ADLS Gen2.
• Proficiency with Kafka and Event Hubs for event streaming.
• Strong knowledge of Data Vault, Star, and Snowflake modeling techniques.
• Experience with DevOps practices, micro-services, CI/CD pipelines, and test automation.
• Ability to use Infrastructure-as-Code tools such as Terraform, ARM, or Bicep.
• Strong foundation in Algorithms, Data Structures, and performance tuning.

Preferred Skills

• Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related technical discipline.
• Experience with Java in addition to Python/Scala.

Key Skills

Education

Bachelor's degree in Computer Science