Senior DevOps Engineer (AWS, Terraform)
Design, build, and maintain core platform components including CI/CD, access management, and compute clusters. Lead the evolution of platform abstraction layers and manage multi-account AWS landing zones.
Design, build, and maintain core platform components including CI/CD, access management, and compute clusters. Lead the evolution of platform abstraction layers and manage multi-account AWS landing zones.
Collaborate with cross-functional teams to design and execute comprehensive test scenarios for AxiomSL regulatory reporting solutions. Perform end-to-end data validation, reconciliation, and defect management to ensure compliance with business and regulatory standards.
Collaborate with cross-functional teams to translate business requirements into ControllerView configurations and support the design of AXIOM regulatory reporting solutions. Analyze and optimize data flows, perform data mapping and reconciliation, and ensure adherence to global regulatory standards.
The Lead DevOps Engineer will mentor AppOps teams, define reliability standards, and manage production incident response. They will also architect observability solutions, automate operational workflows, and partner with cross-functional teams to ensure system performance and security.
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.
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.
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.
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 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.
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.
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.