Design, develop, and maintain scalable backend applications and services using Python, Java, or Golang. Collaborate on cloud-native solutions on AWS while ensuring code quality through testing and architectural contributions.
Develop and maintain scalable data pipelines using SQL-based ELT patterns and optimize transformation logic for curated data marts. Ensure data quality through rigorous testing, orchestration with Airflow, and effective schema evolution using CI/CD practices.
Design and develop high-volume batch and streaming data ingestion pipelines across AWS and GCP platforms. Lead and mentor junior engineers while collaborating with cross-functional teams to build new product features.
Develop responsive, production-ready React applications and translate business requirements into intuitive user interfaces. Collaborate with stakeholders to refine requirements while ensuring high standards for performance, security, and scalability.
Collaborate with stakeholders to translate complex business processes into structured, executable instructions for AI agents. Design, implement, and maintain reusable Claude Code skills while providing technical leadership and defining platform-level standards.
Design and implement end-to-end document intelligence pipelines on AWS while developing and optimizing ML models for document classification and extraction. You will own features from research through production deployment and establish quality metrics for extraction accuracy.
You will perform both manual and automated testing while designing and maintaining test cases for regression and new features. Additionally, you will collaborate with cross-functional teams to ensure high product quality and participate in release readiness discussions.
You will be responsible for hands-on development, automation, and improving the performance and scalability of applications. Additionally, you will manage database optimization, containerized environments, and CI/CD pipelines within an AWS stack.
Design, develop, and maintain scalable backend applications and microservices using Java, Spring Boot, and Quarkus. Implement event-driven solutions on AWS and enhance observability practices within an Agile Scrum environment.
Design and develop scalable backend applications and microservices using Java, Spring Boot, and Quarkus. Implement event-driven solutions on AWS and enhance observability practices within a financial services context.
Collaborate with product management to review requirements and author technical designs and architectures. Contribute to the full SDLC, including code reviews, performance validation, and the optimization of CI/CD frameworks.
Analyze marketing workflows to design and integrate scalable AI-enabled business solutions and Generative AI tools into the MarTech ecosystem. Collaborate with cross-functional teams to define infrastructure requirements, ensure security compliance, and lead technical evaluations of AI vendors.
Assess and document the current Martech ecosystem to identify redundancies and design a consolidated, scalable target-state architecture. Collaborate with cross-functional stakeholders to translate business requirements into practical architecture decisions and implementation plans.
Build and maintain core platform components including SSO, networking, and CI/CD pipelines while managing AWS landing zones and container clusters. Design platform 'golden paths' and provide self-service tools to enable fast and secure deployments for distributed teams.
Assess and document the current Martech ecosystem to identify redundancies and define a simplified, scalable target-state architecture. Collaborate with cross-functional stakeholders to translate business requirements into practical architecture decisions and implementation plans.
Design and maintain scalable ELT pipelines and modern data architectures using dbt and SQL. Collaborate with software engineers to support data-driven applications and manage infrastructure as code via Terraform.
Design and maintain enterprise-grade Java applications and customize Murex components for Capital Markets platforms. Develop real-time and batch integrations while leveraging AI-assisted tools to optimize productivity and code quality.
Act as a liaison between front-office users and technical teams to gather requirements and implement Murex modules. Support trading desks by troubleshooting issues, validating configurations, and optimizing system efficiency.
Design and develop scalable backend applications and microservices using Java, Spring Boot, and Quarkus. Implement event-driven solutions on AWS and support integrations within the Nasdaq Calypso ecosystem.
Design and evolve cloud-native, service-oriented architectures on Microsoft Azure with a focus on scalability and performance. Lead the integration of AI and Generative AI capabilities into core products while driving engineering productivity through intelligent automation.
The Lead Data Engineer will assess data sources and availability to identify ingestion and integration requirements for AI and reporting use cases. They will validate technical feasibility, identify implementation risks, and provide technical documentation and sizing for build activities.
Design, build, and optimize ETL/ELT pipelines to transform data into actionable datasets. Partner with product teams to develop reporting tools and maintain data lakes for ML engineering solutions.
Lead the design, development, and maintenance of scalable Spark applications while enforcing coding standards and best practices. Provide technical leadership through mentoring, code reviews, and regular communication with the client.
Design and evaluate A/B tests and define product KPIs to generate actionable insights from customer behavior data. Collaborate with cross-functional teams to build reporting solutions and support data-driven product strategy.
Develop and maintain core products using Python, TypeScript, and Java/Spring within a cross-functional Agile team. Contribute to architectural decisions, system modernization, and ensure high software quality through testing and code reviews.
Serve as a subject matter expert in commodities trading to support front-office workflows and operational processes. Collaborate with traders and technology teams to gather requirements, document functional specifications, and drive system enhancements.
Design, develop, and maintain scalable Spark applications while enforcing coding standards and best practices. Collaborate with cross-functional teams to deliver high-quality software solutions and maintain comprehensive technical documentation.
Design and develop internal tools, AI-powered applications, and workflow automations to support sales enablement and internal offerings. Collaborate with data scientists and stakeholders to productionize prototypes and improve system reliability and observability.
