Senior Data Architect

Risk : Market Data Derivatives Platform Market Risk Derivatives Risk Data For Risk engines Market Risk calculations Market Data Handling Fixed income Equities Valuations Yield Curve Analysis
Excellent domain knowledge in Market Risk and Front-office Risk Domains
Experience in developing Market Risk Analytics Platforms

Mandatory Areas
Must Have Skills
Skill 1 15 Yrs of Exp data architecture data engineering or a similar role with a proven track record of designing and delivering large-scale data solutions.
Skill 2 15 Yrs of Exp Market Risk and Front-office Risk Domains
Skill 3 15 Yrs of Exp developing Market Risk Analytics Platforms
Skill 4 15 Yrs of Exp Snowflake including performance tuning security best practices and cost management.
Skill 5 15Yrs of Exp AWS ecosystem including S3 EC2 Lambda Glue IAM and networking fundamentals.
Skill 6 15Yrs of Exp Python for data manipulation pipeline development and automation.
Skill 7 15Yrs of Exp architecting and delivering data solutions for BI and analytics with direct experience using tools like Sigma and/or Power BI.
Skill 8 15Yrs of Exp experience and deep domain knowledge of financial services back-office operations specifically within Risk Management (e.g. trade lifecycle settlement risk counterparty data collateral).
Skill 9 15Yrs of Exp data architecture patterns (e.g. Data Warehousing Data Lake Data Mesh) data modeling and data governance principles.
Skill 10 15Yrs of Exp data security principles and implementation including data encryption (at-rest in-transit) tokenization and managing Material Non-Public Information (MNPI).
Skill 11 15Yrs of Exp data transformation tools like dbt (Data Build Tool).
Skill 12 15Yrs of Exp infrastructure-as-code (IaC) tools such as Terraform or CloudFormation.
Skill 13 15Yrs of Exp streaming data technologies (e.g. Kafka Kinesis).
Skill 14 15Yrs of Exp financial instruments across equities fixed income and derivatives.

Mandatory if Applicable
Domain Experience (If any ) :-Yes-Core Risk Management Service


Location- Jersey City NJ
Number of days onsite -Day 1 Onsite Candidate needs to work 5 Days at the Client Office
If Onsite Office Address - 101 Hudson St Jersey City NJ 07302

The Role

The Risk Management Back Office is the operational core of the risk ecosystem responsible for the integrity settlement and reporting of all trading activity. This team ensures the foundational data that underpins a firms risk analysis is accurate timely and secure. We are seeking an exceptional Senior Data Architect to lead the design and implementation of a next-generation data platform for our financial services clients directly enabling robust risk mitigation regulatory compliance and operational excellence.

Position Summary

As a Senior Data Architect you will be the primary owner of the data architecture for the Risk Management Back Office. You will leverage your deep expertise in modern cloud data platforms and financial risk management to design and build scalable secure and resilient data solutions on AWS and Snowflake. This role requires a hands-on leader who can architect enterprise-grade systems establish rigorous data governance and quality frameworks and collaborate effectively with stakeholders across the front middle and back office.

Key Responsibilities

• Architect & Design: Design build and maintain the end-to-end data architecture for the Risk Management Back Office leveraging AWS and Snowflake to support critical functions of Risk : Market Data Derivatives Platform Market Risk Derivatives Risk Data For Risk engines Market Risk calculations Market Data Handling Fixed income Equities Valuations Yield Curve Analysis
• Data Modeling & Pipelines: Develop conceptual logical and physical data models for risk data domains. Lead the development of complex high-performance data ingestion and transformation pipelines using Python (including Snowpark) and AWS data services (e.g. Glue Lambda Kinesis).
• Governance & Quality: Establish and champion a robust data governance framework. Define and enforce standards for data lineage metadata management and data quality. Implement monitoring and alerting systems to ensure the highest levels of data integrity.
• Business Intelligence & Analytics: Partner with Market risk Business operations teams and leadership to understand their data needs. Architect data marts and semantic layers optimized for analytics and support the development of insightful dashboards and reports using Sigma Power BI and other BI tools.
• Security & Compliance: Serve as a subject matter expert on data security within the data platform. Design and implement solutions for data classification access control and protection ensuring compliance with firm policies and financial regulations.
• Technical Leadership: Provide technical guidance and mentorship to data engineers and analysts. Champion best practices in data architecture software engineering and cloud infrastructure. Drive innovation by evaluating and adopting new technologies and methodologies.

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.
• Excellent domain knowledge in Market Risk and Front-office Risk Domains
• Experience in developing Market Risk Analytics Platforms
• 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.
• 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