Senior Data Integration Engineer - Credit Risk Experience

Compu-Vision Consulting Inc.

New York City, NY

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JOB DETAILS

SALARY

$640–$650 Per Day

SKILLS

Agile Programming Methodologies, Analysis Skills, Apache Kafka, Apache Spark, Atlassian JIRA, Automation, Banking Services, Business Analysis, Capacity Management, Cisco Unity, Cloud Computing, Communication Skills, Computer Programming, Computer Skills, Continuous Deployment/Delivery, Continuous Improvement, Continuous Integration, Credit Risk, Data Analysis, Data Lake, Data Management, Data Migration, Data Modeling, Data Processing, Data Quality, Data Warehousing, Database Extract Transform and Load (ETL), Derivatives, Detail Oriented, DevOps, EAD, Enterprise Data Integration, Establish Priorities, Financial Services, Industry/Trade Analysis, Interpersonal Skills, Jenkins, Knowledge Transfer, Machine Tool, Marketing/Sales Collateral, Microsoft Windows Azure, Migration Strategy, Multicultural, Multiplatform/Cross-Platform, Multitasking, Operational Improvement, Power BI, Presentation/Verbal Skills, Problem Solving Skills, Process Improvement, Python Programming/Scripting Language, Reconciliation, Regulations, Regulatory Reports, Risk, Risk Analysis, Root Cause Analysis, SQL (Structured Query Language), Software Development, Stored Procedures, Strategic Planning, Stress Testing, Structured Data, System Architecture, System Integration (SI), Team Player, Technical Delivery, Technical Writing, Time Management, Writing Skills

LOCATION

New York City, NY

POSTED

30+ days ago

W2 Only
Location – NYC
6 months and extendable
In-person interview is mandatory.

Job Description -

We are seeking a senior Counterparty Credit Risk (CCR) Data Integration Engineer to assume end to end accountability for stable, resilient, and observable data integration pipelines across CCR technology platforms.

Major Responsibilities:

Design, develop, maintain and optimize scalable data pipelines to ingest, transform, and integrate counterparty, trade, collateral and market data from upstream systems (Systems Of Record) for CCR exposure analytics (e.g., EPE, PFE, EAD, sensitivities).
Implement robust ETL/ELT solutions for structured and semi structured data across batch and streaming processes using enterprise data platforms (e.g., data lakes, data warehouses, and distributed processing frameworks).
Support integration of trading and derivatives data (e.g., exposures, collateral, netting, margin) into CCR calculation and reporting platforms.
Partner with EM and CRR users and business analysts to understand business requirements related to exposure, PFE, EAD, and stress testing.
Enable accurate, consistent, validated CCR data for EPE/PFE calculations, limit monitoring, what if pre-trade intraday analysis, and regulatory and HO reporting.
Deliver timely enhancements to ETL pipelines, CCR data models, data lineage, and controls aligned with the EM users' and regulatory expectations (e.g., Basel regulations).
Implement data quality checks, reconciliations, and monitoring to ensure completeness, accuracy, and timeliness of CCR data (Data governance and compliance).
Proactively identify and execute opportunities for process standardization/optimization, tooling enhancements, and operational simplification across the CCR application stack.
Lead by example in technical documentation, knowledge transfer, implementation standards, data management, and control frameworks, reducing dependency on key individuals and ensuring service quality, productivity, and continuous skill development.
Proactively investigate, identify root cause of recurring incidents, and resolve data issues across upstream and downstream systems, working with IT and business stakeholders.
Demonstrate a continuous improvement mindset through their example, with a focus on reducing incidents, manual interventions, and operational risk, and improving turnaround time for incidents.
Drive root cause analysis (RCA) for impactful incidents (Calculation breaks, data validation/reconciliation issues), ensuring recurring issues are eliminated through permanent fixes rather than short term workarounds.
Champion automation and self healing for batch monitoring, data validation, reconciliations, and recovery processes for production as well as lower testing environments.
Partner with BAU Ops and Infrastructure teams to improve data transparency, and observability, alerting, capacity planning, and resilience of CCR platforms.
Ensure DR/BCP readiness for EM critical systems, including regular/annual testing and documented recovery procedures.
Work closely with EM and CRR users, Business Analysts, Risk Analytics, and Technology teams to deliver end to end data solutions.
Take initiative and come up with enhancement proposals and lead platform migrations, and strategic data initiatives.
Support audit, regulatory, and ad hoc data requests related to counterparty credit risk.

Required Qualifications:

10+ years of strong programming experience in Python and advanced SQL, with a focus on data transformation and analytics.
5+ years of experience in data engineering, data integration, or enterprise data management within financial services.
3+ years in a VP level or equivalent senior role supporting risk or exposure platforms.
3+ years of hands on experience with Databricks and PySpark for large scale ETL and data integration.
Demonstrated experience operating global, offshore leveraged support models in a regulated environment.

Technical & Domain Expertise :

Proficient understanding of Exposure Management and Counterparty Credit Risk concepts, including derivative trade cycles, market data, EPE, PFE, EAD, netting, Collateral/margin management, limits, stress testing, and what if analysis.
Experience supporting batch intensive and intraday real time risk platforms (Python, PySpark, ETL, Tidal, Stored Procedure, SQL, Snowflake, PowerBI).
Demonstrated experience designing and managing Databricks, Medallion Architecture, Unity Catalog, Workflows/Orchestration, including complex DAGs and dependencies (Exposure to Astronomer/Airflow is a plus).
Hands-on experience with Cloud computing and infrastructure (Azure, Data Lake, ADF, Kafka, Spark based distributed compute, other Cloud native technologies).
Experience implementing CI/CD pipelines using Jenkins, GitLab CI, or Azure DevOps in a data engineering environment.
Familiarity with regulatory risk data principles and expectations for banking institutions (e.g., aggregation, reconciliation, and auditability of risk data).
Proven track record taking initiative and driving a technological transformation project with an Agile based application/software development.
Proven ability to utilize JIRA, Confluence to manage tasks, technical documentation, production incidents, and releases.

Leadership & Soft Skills :

Demonstrated continuous improvement mindset, with the ability to drive cultural change across the engineering team.
Strong experience collaborating with distributed, multicultural global teams and third party vendors.
Excellent interpersonal, written and verbal communication skills with the ability to work with both technical and non technical stakeholders, and senior Technology team leads.
Ability to prioritize and effectively manage multiple tasks under time-critical and regulatory pressure.
Highly motivated, self-directed individual with the ability to work independently and in team environments.
Effective presenter capable of articulating high level concepts to strategic execution plans including system/architecture/data flow diagrams, combined with extreme attention to detail.
Strong analytical, problem solving (breaking ambiguous/large problems to smaller/less complex ones), and decision-making skills.
Collaborative team player and relationship builder.

About the Company

Compu-Vision Consulting Inc.

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