Title: Market Data Senior Java Developer Location: New York, NY (1271 AOA/6th Ave) Job Description: This is an exciting opportunity where you would be part of several green field initiatives such as building dashboards for different market data sets and helping to bring traceability and auditing of the market data flow through the systems. In this role, you will interact directly with trading, quantitative, compliance and risk, and IT functions to deliver new market data capabilities and services leveraging modern technologies and data & software architectures. Key Responsibilities: - Hands on Senior Java Developer with over 5 years of enterprise development experience - Work with multiple business teams including trading and quantitative analysts - Provide work estimates as needed - Develop system architectures, designs and concepts - Maintain and improve code quality using static & dynamic code analyses, security vulnerability scans, code coverage and CI/CD pipeline gating - Design, build and configure applications to meet business process and application requirements - Participate in all phases of software delivery lifecycle from analysis through support. Required Skills: - Experienced server-side Java Developer (JDK 11 or 17) - Spring (including Spring Boot and Spring Boot Actuator) - Experience with asynchronous, event-driven programming & concurrency - REST API (including Enterprise Authentication and Authentication) - JMS (Active MQ or similar) - MS SQL Server and/or Sybase experience Preferred Skills: - Experience designing and supporting low latency, high throughput trading applications - Apache Camel (Version 3 or 4) - Enterprise services (including monitoring, state management) - Experience integrating proprietary components with Bloomberg or Murex - MS SQL Server and/or Sybase experience - Experience with Capital Markets Education: Bachelor degree in Mathematics, Engineering or Computer Science. The expected base salary ranges from $111k-$220k. 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. #LI-Hybrid 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.

Role Description The Vice President, Data Architecture is a hands-on technology leader responsible for defining, building, and scaling Accuity’s enterprise data platforms, data architecture, data applications, data pipelines, and analytics enablement capabilities. This role’s top priority is leading Accuity’s migration from its SQL Server based architecture to a modern Databricks lakehouse, reducing technical debt and platform cost while improving scalability and performance. Responsibilities - Strategy and Data Architecture Leadership - Lead the design, development, and evolution of Accuity’s Azure-based enterprise data architecture. - Own the data platforms, data architecture, data applications, data pipelines, and analytics enablement capabilities. - Establish scalable data architecture standards, patterns, and governance practices. - Translate business requirements into data platform strategies, technical designs, program enhancements, and delivery roadmaps. - Partner with the CTO and Technology leadership to prioritize data initiatives. - Evaluate current and future data platform needs and recommend improvements. - Identify and lead initiatives to reduce data platform infrastructure and licensing costs. - Data Platform, Engineering, and Analytics Enablement - Lead data-centric initiatives supporting SaaS applications, ETL processes, and enterprise analytics. - Design, build, and optimize data applications, data platforms, data pipelines, and reporting infrastructure. - Provide hands-on technical leadership for Azure database administration and optimization. - Develop and guide the development of database solutions. - Lead the migration and phased decommission of legacy database objects. - Analyze structural requirements for new data applications and analytics solutions. - Improve data system performance through testing, troubleshooting, and optimization. - Define and maintain appropriate data security, backup, recovery, and operational support procedures. - Support operational reporting and Management Information Systems needs. - AI/ML Enablement and Data Science Partnership - Own the data architecture and platform capabilities required to enable AI/ML development. - Partner closely with the VP, Data Science & AI to support Accuity’s data science strategy. - Collaborate with Data Science to operationalize models. - Coordinate cross-functional stakeholders to launch data, analytics, and AI/ML enablement initiatives. - Ensure clear ownership boundaries between Data Architecture and Data Science. - Leadership and People Management - Lead the day-to-day operations, staffing, training, quality, productivity, and performance of the Data Architecture team. - Own and lead the Data Engineering and Data Operations functions. - Serve as a player-coach by balancing team leadership with hands-on technical contribution. - Foster a collaborative, inclusive, accountable, and growth-oriented team culture. - Set clear goals, priorities, deliverables, and performance expectations for team members. - Support team development through coaching, feedback, and technical guidance. - Cross-Functional Collaboration - Collaborate with Application Development, Data Science, Operations, Finance, and third-party partners. - Serve as a senior technical advisor on data architecture and analytics enablement. - Gather requirements from stakeholders and translate those into effective data solutions. - Coordinate multiple parties to deliver data initiatives. - Communicate technical recommendations clearly to various audiences. - Compliance, Security, and Quality - Promote data quality, accuracy, integrity, consistency, and reliability. - Oversee periodic data cleansing and related data quality improvement activities. - Ensure data platforms and processes are designed with appropriate controls and security measures. - Support compliance-aligned data practices appropriate for healthcare technology. - Partner with security, compliance, and technology stakeholders. - Other Duties as Assigned - Perform miscellaneous job-related duties as assigned. Qualifications - Bachelor’s degree in Computer Science, Business Intelligence, Engineering, Mathematics, Information Systems, or a related field preferred. - Relevant technical certifications in Azure, database administration, data architecture, data engineering, analytics, security, or related disciplines preferred. - Minimum of 10 years of progressive experience in data architecture, database architecture, data engineering, or database administration. - Minimum of 3 years of Azure-based data platform experience. - Minimum of 5 years of experience leading or managing technical teams. - Experience supporting data architecture or data engineering capabilities for analytics, reporting, or AI/ML enablement. - Healthcare, healthcare revenue cycle, SaaS, or technology-enabled services experience preferred. - Experience supporting secure or regulated data environments preferred. Core Competencies - Strategic Data Leadership - Player-Coach Leadership - Technical Judgment - People Leadership - Cross-Functional Collaboration - Communication - Problem Solving - Execution Discipline - Remote-Work Effectiveness - Compliance and Risk Awareness - Migration and Change Leadership - Adaptability Additional Requirements - Physical Requirements: Interaction with people and technology while either sitting or standing. - Position and Employment Statement: Management reserves the right to modify, add or remove duties from a job.

Role Description We are hiring a hands-on data engineering leader to lead and scale TRANZACT's data engineering teams and pioneer a new AI-first data engineering discipline—accelerating the velocity, quality, and business impact of everything we build on data. You will own the architecture, delivery, governance, and security of our modern data platform built on Databricks and PostgreSQL, while embedding AI into how our teams design, build, and operate data systems. This role combines strategic platform ownership with sleeves-rolled-up execution and people leadership. What You'll Own (Systems-Level Outcomes) - Define and evolve the end-to-end data platform strategy across ingestion, transformation, storage, and serving—anchored on Databricks (Lakehouse, Delta, Unity Catalog) and PostgreSQL—with production-grade reliability and cost efficiency. - Establish an AI-first data engineering practice: standard patterns, SDKs, and golden paths that use AI to accelerate pipeline development, testing, documentation, and operations across teams. - Stand up enterprise-grade data governance and data security: cataloging, lineage, access controls, data quality, PII handling, and policy enforcement across the platform. - Build and lead high-performing data engineering teams—hiring, mentoring, and setting the technical bar—while driving measurable improvements in delivery velocity and platform trust. - Uplift the broader Engineering and Data organizations by sharing reusable components, best practices, and self-service capabilities that reduce bottlenecks and vendor dependency. - Serve as the accountable leader for critical data initiatives, driving requirements → architecture → implementation → launch → post-launch learning. Key Responsibilities - Architect scalable, reliable data pipelines and platform services on Databricks and PostgreSQL, supporting batch and streaming workloads across marketing, sales, and servicing domains. - Define and roll out an AI-first engineering workflow—leveraging AI coding assistants, agentic tooling, and automated eval/QA gates—to accelerate data engineering outcomes without compromising quality or security. - Establish data governance standards: Unity Catalog (or equivalent), lineage, data contracts, freshness and quality SLAs, and asset lifecycle management. - Own data security posture in partnership with Security and Compliance: role-based access, audit trails, encryption, PII/PHI handling, and regulatory alignment appropriate to insurance data. - Set engineering standards and review designs, PRs, data models, and architecture; drive adoption through documentation and enablement. - Lead vendor and tooling evaluation, and make build/buy/insource recommendations aligned to unit economics, reliability, and IP strategy. - Recruit, mentor, and develop engineers; host tech talks and cultivate a culture of ownership, experimentation, and continuous improvement. Success Profile (6–12 Months) - The data platform reliably supports key production use cases with clear SLOs, runbooks, and cost visibility. - An AI-first engineering practice is established, with reusable templates and golden paths measurably increasing delivery velocity across teams. - Data governance and data security controls are standardized, auditable, and enforced across the platform. - Teams are staffed, aligned, and performing, with healthy delivery and quality signals. - At least one critical data initiative is led to launch with documented business impact and a retrospective feeding the platform roadmap. Qualifications - 10+ years in data engineering or related distributed systems; 4+ years leading and building data engineering teams. - Proven, hands-on experience leveraging AI to accelerate data engineering outcomes (e.g., AI coding assistants, agentic tooling, LLM-assisted pipeline development, testing, or operations). - Deep expertise with Databricks or equivalent (Lakehouse, Delta Lake, Spark, Unity Catalog) and PostgreSQL in production. - Demonstrated ownership of data governance and data security programs: cataloging, lineage, access control, data quality, and PII handling. - Strong engineering fundamentals in Python and SQL; experience designing scalable ETL/ELT and streaming architectures. - Track record of setting technical standards and delivering complex data initiatives from architecture through launch. - Excellent communicator and mentor, effective with stakeholders across technical and non-technical domains. - Bachelor's degree in Computer Science or related field required. Preferred Qualifications - Master's degree in Computer Science, Data Engineering, or a related field. - Experience in insurance, healthcare, or other regulated, data-sensitive industries. - Experience with Apache Airflow (or comparable orchestration frameworks) and SQL Server in production. - Cloud-native experience on Azure and/or AWS, with strong infrastructure-as-code practices (e.g., Terraform, Bicep, CloudFormation). - Familiarity with data observability, dataset versioning, and approval/quality gates. - Exposure to ML/AI platform enablement (feature stores, model registries) supporting data science teams. How We Work - AI-first: we use AI to accelerate engineering while protecting proprietary data and process IP. - Agile and iterative: prove value quickly, then scale with governance and reliability. - Responsible by default: governance, lineage, permissions, security, and continuous evaluation built in from the start. Compensation and Benefits - The base salary compensation being offered for this role is $200,000 USD per year. - This role is also eligible to participate in the annual bonus program. Company Benefits - Health and Welfare Benefits: Medical (including prescription coverage), Dental, Vision, Health Savings Account, Health Care and Dependent Care Flexible Spending Accounts, Group Accident, Group Critical Illness, Life Insurance, AD&D, Group Legal, Identify Theft Protection, Wellbeing Program and Work/Life Resources (including Employee Assistance Program). - Leave Benefits: Paid Holidays, Annual Paid Time Off (includes state/local paid leave where required), Short-Term Disability, Long-Term Disability, Other Leaves (e.g., Bereavement, FMLA, ADA, Jury Duty, Military Leave, and Parental and Adoption Leave). - Retirement Benefits: Savings Plan with annual nonelective company contribution. TRANZACT is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Equal Opportunity Employer/Disability/Vet

• Work with technologies that ensure our data pipeline efficiently maintains and calculates data for the 7 million+ securities in our universe. • Work on features that ensure financial data is consistent, reliable, timely and accurate by importing data from third party data providers and performing custom calculations on this imported data, with day-to-day emphasis on database load management, caching strategies, memory efficiency, and query optimization. • Write code (and unit tests!) in Python and the Django framework to implement complex backend features. • Use tools like Airflow to build / enhance financial data pipelines for over 7 million securities. • Make use of pandas and asynchronous task tools like celery to efficiently calculate 4,000+ unique data points for each security. • Profile and optimize database queries — analyze query plans, design effective indexes, and eliminate N+1s and slow paths that don't hold up under production load. • Manage database load — reason about read/write patterns, connection usage, replica strategy, and batching to keep the data tier healthy as volume grows. • Design and tune caching layers to reduce redundant computation and database pressure while keeping data fresh and correct. • Design robust, scalable data models that account for the structure, type, and volume of data to store, and how it will be queried. • Investigate and resolve performance regressions and incidents — using metrics, profiling, and monitoring to find root causes. • Design, plan, estimate, and ticket features that are scoped by our product team. • Perform code reviews for other engineers on the team. • Document the work you have done both in repo as well as outside of the repo for future engineers. • Collaborate with other engineers both verbally and in writing to plan, design, and build a world-class financial research platform.