Senior Data Engineer - Credit Risk (Hybrid) - New York, NY
Job Description
Job DescriptionSenior Data Engineer – Credit Risk (Hybrid)
Location: New York, NY 10020 (Hybrid)
Duration: 1-Year Contract (Possible Extension)
Interview Process: 2 Virtual Teams Interviews + 1 Onsite Interview
Position Overview
"Navitas Partners, LLC" is seeking a highly experienced Senior Data Engineer to join a Credit Risk technology team supporting enterprise-scale risk data platforms. The ideal candidate will lead architecture discussions, design scalable data pipelines, and ensure reliable, compliant, and high-quality data processing across modern cloud-based lakehouse environments.
This role requires deep expertise in financial data engineering, credit risk domains, and large-scale distributed data processing using PySpark and Databricks.
Key Responsibilities
- Lead architecture and technical design discussions for Credit Risk data platforms using modern data engineering frameworks and cloud-native technologies
- Design and implement scalable batch and streaming data pipelines using PySpark within a Medallion Lakehouse architecture on Databricks
- Build and maintain data ingestion pipelines from upstream systems (loan origination, trading systems, market data feeds) into cloud storage (S3/ADLS) using Parquet and Delta Lake formats
- Implement partitioning strategies, Z-order optimization, and schema evolution for high-performance data processing
- Develop and optimize large-scale PySpark transformations for credit and counterparty risk datasets ensuring accuracy, auditability, and regulatory compliance across Bronze, Silver, and Gold layers
- Support modeling and optimization of risk metrics including PD, LGD, EAD, EPE, PFE, CVA for downstream analytics and reporting
- Integrate with external risk/XVA engines and manage orchestration of long-running batch computations
- Ensure platform reliability, observability, lineage tracking, security, and regulatory compliance (Basel III/IV, FRTB, CECL)
- Design and maintain APIs, data contracts, and technical documentation aligned with audit and compliance standards
- Collaborate closely with risk, quant, compliance, and engineering teams to deliver scalable data solutions
Required Qualifications
- 12+ years of experience in data engineering or data development, preferably in financial services or banking
- Strong domain expertise in Credit Risk and Counterparty Risk
- Familiarity with regulatory frameworks such as Basel III/IV, IFRS 9, CECL, FRTB
- Expert-level proficiency in Python and PySpark/Apache Spark
- Hands-on experience with Azure Databricks, Delta Lake, and Medallion Architecture
- Strong SQL skills including joins, window functions, and performance optimization on large datasets
- Experience building ingestion pipelines from core banking, trading, and market data systems
- Knowledge of workflow orchestration tools such as Airflow or Databricks Workflows
- Experience with CI/CD tools including Git, Jenkins, and Azure DevOps in regulated environments
- Understanding of cloud platforms (AWS certification or equivalent preferred)
- Experience producing architecture diagrams, data flow documentation, and data dictionaries
- Agile delivery experience using tools such as JIRA, Confluence, and Zephyr
- Strong communication skills with ability to bridge technical and risk/business stakeholders
Preferred Attributes
- Strong focus on data governance, data quality, and regulatory compliance
- Experience working with quant teams and risk modeling systems
- Ability to quickly adapt to evolving financial technologies and regulatory requirements
- Proactive, collaborative, and detail-oriented mindset in high-stakes environments
For more details reach at resumes@navitassols.com
About Navitas Partners, LLC: It is a certified WBENC and one of the fastest-growing Technical / IT staffing firms in the US providing services to numerous clients. We offer the most competitive pay for every position. We understand this is a partnership. You will not be blindsided and your salary will be discussed upfront.