Top Tech Jobs & Startup Jobs

Leads end-to-end technology release management across multiple applications and delivery teams. Responsibilities include integrated planning, scheduling, dependency and risk management, readiness reviews, governance, approvals, deployment and rollback coordination, executive reporting, production support preparation, hypercare tracking, and continuous improvement. The role coordinates Business, Product, Development, Infrastructure, Change Management, SRE, UAT, and support stakeholders to ensure predictable, controlled, and low-risk releases.

Leads IT executive communications, strategic messaging, town halls, leadership forums, and cross-functional alignment. Translates complex technology initiatives into clear narratives, supports change management, and improves information flow and operational processes. Partners with senior IT leaders, Corporate Communications, and business units while coordinating talent and engagement initiatives. The role requires executive writing, stakeholder engagement, project management, process improvement, and operational leadership.

Designs, develops, tests, deploys, and maintains scalable enterprise applications, data platforms, cloud-native solutions, web applications, APIs, and microservices. Leads Snowflake data engineering, AWS architecture, CI/CD modernization, observability, troubleshooting, technical design, and architecture reviews. Uses AI-assisted development tools, mentors engineers, establishes engineering standards, and partners with cross-functional stakeholders to deliver secure, resilient, high-performance solutions.

Leads the global IAM engineering organization, defining enterprise roadmaps and standards across authentication, authorization, privileged access, identity governance, directory services, cloud identity, and human/non-human identities. Oversees resilient platform delivery, observability, automation, service reliability, regulatory controls, and modernization across hybrid environments. Partners with senior technology leaders, develops engineering talent, advances AI-enabled automation, and manages security and operational risks in a regulated environment.

Lead reliability and observability initiatives across enterprise applications. Implement monitoring (Splunk, Grafana, Dynatrace, ITSI), define SLIs/SLOs, drive incident response and RCA, build automation and AI-assisted self-healing, partner with engineering/cloud/security for resiliency and performance.

Leads market risk management for DTCC clearing organizations, overseeing member exposures, margin requirements, liquidity needs, risk controls, regulatory compliance, model risk, and remediation. Manages a distributed market risk team, advises risk committees and senior management, presents metrics to regulators, and leads complex projects and process enhancements supporting financial market stability and new products.

Leads the creation and development of DTCC’s enterprise Category Management function. Establishes operating models, governance, category strategies, supplier risk practices, analytics, and performance reporting. Builds and manages a high-performing procurement team while advising senior leaders, driving cost optimization, supplier innovation, resilience, and procurement transformation across enterprise spend categories.

Provides production application support across mainframe, cloud, Unix, Linux, and Windows environments. Leads major incident resolution, troubleshooting, root-cause analysis, monitoring, disaster recovery, audit support, certificate management, and operational readiness. Maintains dashboards, runbooks, and knowledge articles while identifying automation opportunities. Collaborates with development, infrastructure, and business teams to improve application resiliency, security, observability, and supportability in a highly regulated financial-services environment.

Supports enterprise data programs involving master and reference data, data governance, stewardship, lifecycle management, quality, reporting, analytics, and modernization. Analyzes data, processes, requirements, and stakeholder needs; documents business requirements and data definitions; partners with business, technology, and data teams; and contributes to reporting, process improvements, platform enhancements, and cross-functional initiatives. This is an 18-month early-career program for students graduating in May 2027.

Designs and implements enterprise database blueprints and data models. Serves as a subject matter expert on data content, quality, relationships, and future usage. Partners with technology, analytics, and business teams to manage model evolution, schema refactoring, dimensional design, and Snowflake deployments. Applies normalization, Kimball methodology, semantic modeling, SQL, data profiling, cloud technologies, and Agile practices within a distributed data architecture team, preferably in financial services.