Senior Data Architect- Risk Management Office

Overview

On Site
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - 12 Month(s)
No Travel Required

Skills

AWS
Azure
Python

Job Details

 

Role: Senior Data Architect- Risk Management Office Location:- New York City, NY or Jersey City, NJ (Day 1 Onsite- Candidate Needs to work 5 Days at the Client Office)

Duration: 12+ Months

 

Interview Mode- 2 UST (Video)+ 1st client round (Video)+ 2nd client round (In- Person) Note from the Client:- Candidate should have extensive experience and deep domain knowledge of financial services back-office operations, specifically within Risk Management (e.g., trade lifecycle, settlement risk, counterparty data, collateral).
Required Qualifications & Skills

  • 15+ years of experience in data architecture, data engineering, or a similar role, with a proven track record of designing and delivering large-scale data solutions.
  • Extensive, hands-on experience with Snowflake, including performance tuning, security best practices, and cost management.
  • Expert-level knowledge of the AWS ecosystem, including S3, EC2, Lambda, Glue, IAM, and networking fundamentals.
  • Advanced programming proficiency in Python for data manipulation, pipeline development, and automation.
  • Demonstrable experience architecting and delivering data solutions for BI and analytics, with direct experience using tools like Sigma and/or Power BI.
  • Crucially, extensive experience and deep domain knowledge of financial services back-office operations, specifically within Risk Management (e.g., trade lifecycle, settlement risk, counterparty data, collateral).
  • Expert-level understanding of data architecture patterns (e.g., Data Warehousing, Data Lake, Data Mesh), data modeling, and data governance principles.

Preferred Qualifications

  • Deep, practical experience with data security principles and implementation, including data encryption (at-rest, in-transit), tokenization, and managing Material Non-Public Information (MNPI).
  • Experience with data transformation tools like dbt (Data Build Tool).
  • Familiarity with infrastructure-as-code (IaC) tools such as Terraform or CloudFormation.
  • Knowledge of streaming data technologies (e.g., Kafka, Kinesis).
  • Strong understanding of financial instruments across equities, fixed income, and derivatives.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.