Credit Risk Technology - Risk Data Integration Engineer

Join Mizuho as a Credit Risk Technology – Risk Data Integration Engineer! Credit Risk Technology at Mizuho Americas is 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. In this role, you will be responsible for designing, building, integrating, and operating robust and scalable data architecture, model, and pipelines that support Exposure Management (EM), Credit Risk Reporting (CRR), Risk Analytics, Front Office users, and Regulatory Reporting. The position plays an essential role in delivering reliable data transformation processes for exposure calculation, limit monitoring, and intraday what‑if analysis capabilities across OTC, Exchange‑Traded Derivatives (ETD), and Securities Financing Transactions (SFT). This role focuses on integrating trade, counterparty, collateral, and market data into curated risk data layers used for exposure calculation, limit monitoring, stress testing, and regulatory reporting. The successful candidate will lead by example, work with a strong ownership/proposal mindset, and drive a technology modernization program to transform the legacy platform into the high‑availability, high‑performance, robust, scalable analysis platform with automated controls for data validation, data completeness, and traceable data lineage. The ideal candidate must be a seasoned data integration engineer who is technically proficient, able to multi‑task effectively, and capable of clearly articulating complex problems and solutions. The role requires a collaborative, can‑do attitude and the ability to align day‑to‑day execution with a broader strategic vision. 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. Counterparty Credit Risk Support 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). Data Quality, Controls & Governance 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. Incident, Problem & Change Management 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. Enforce robust change and release governance aligned with Mizuho Americas CAB, DevOps, CI/CD, risk, audit and control standards, eliminating production release incidents and continuously enhancing release processes to mitigate the risk. Platform Reliability, Automation & Resilience 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 Experience Bachelor’s Degree in Computer Science, Management of Information Systems, or related business discipline(s). 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. The expected base salary ranges from $111,000-$155,000. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, and, where applicable, certifications and licenses obtained. Market and organizational factors are also considered. In addition to salary and a generous employee benefits package, successful candidates are eligible to receive a discretionary bonus. Other requirements Mizuho has in place a hybrid working program, with varying opportunities for remote work depending on the nature of the role, needs of your department, as well as local laws and regulatory obligations. Roles in some of our departments have greater in‑office requirements that will be communicated to you as part of the recruitment process. #J-18808-Ljbffr Mizuho Bank, Ltd.