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Manager, Enterprise Data Platform

Intercontinental Exchange · Atlanta, GA, US

remoteunknownPosted Sep 11, 2026PythonSQLKubernetesJenkinsCI/CDGit

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About this role

## Overview ICE Data Services provides global securities evaluations, reference data, and analytics that support financial institutions and investment funds across valuation, securities operations, research, and portfolio management. The **Enterprise Data Architecture** team is seeking a **Software Development Manager** to lead engineering for ICE Data Services’ next-generation enterprise data platform. ## What You’ll Do - Lead, mentor, and manage a team of software and data engineers building enterprise data platform capabilities. - Translate strategic platform objectives into engineering roadmaps, delivery plans, milestones, and measurable outcomes. - Deliver scalable, secure, maintainable, and reliable platform services (e.g., orchestration, pipeline automation, testing frameworks, reusable integration patterns). - Partner with enterprise architecture, infrastructure, product, data governance, QA, ML/AI, and business stakeholders to align priorities with organizational needs. - Establish and enforce engineering best practices across version control, CI/CD, automated testing, code review, observability, deployment readiness, and production support. - Drive **self-service** platform capabilities so teams can create, deploy, and operate data pipelines with guardrails and reduced centralized dependency. - Champion data quality, metadata, lineage, schema governance, data contracts, and lifecycle management. - Manage technical risk, dependencies, resource planning, release planning, and operational readiness. - Recruit, hire, onboard, and retain talent; support career development, performance management, and succession planning. - Build a culture of accountability, collaboration, engineering excellence, continuous improvement, and business-impact delivery. - Serve as an escalation point for critical platform issues, operational incidents, delivery risks, and cross-team blockers. - Communicate priorities, status, risks, and outcomes clearly to senior leadership and cross-functional partners. ## Knowledge & Experience - Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Information Systems, Data Science, Engineering, or related field. - **8+ years** of professional software engineering, data engineering, or platform engineering experience. - **2+ years** leading/managing engineering teams (performance management, hiring, mentoring, delivery accountability). - Experience managing enterprise-scale data platforms, distributed systems, workflow orchestration, shared platform services, or large-scale infrastructure. - Strong understanding of modern software engineering practices (SDLC, Agile, CI/CD, automated testing, code quality, release management, production support). - Familiarity with data engineering concepts (pipeline orchestration, batch/real-time processing, transformations, data quality frameworks, testing strategies). - Experience with containerized/Kubernetes environments, infrastructure automation, monitoring/alerting, and operational reliability. - Working knowledge of **SQL** and **Python**, data modeling, data warehouse design, and enterprise integration patterns. - Understanding of data governance (metadata, lineage, schema governance, data contracts, entitlement/auditability, compliance controls). - Ability to work cross-functionally with architects, product, infrastructure, QA, data scientists, ML engineers, and business stakeholders. - Strong communication skills across technical and non-technical aud

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