Overview
Job Purpose
We''re seeking a talented Senior Data Engineer to join our Enterprise Architecture team in a cross-cutting role that will help define and implement our next-generation data platform. In this pivotal position, you''ll lead the design and implementation of scalable, self-service data pipelines with a strong emphasis on data quality and governance. This is an opportunity to shape our data engineering practice from the ground up, working directly with key stakeholders to build mission-critical ML and AI data workflows.
Responsibilities
- Design, build, and maintain our on-premises data orchestration platform using the best-in-breed open source tools
- Create self-service capabilities that empower teams across the organization to build and deploy data pipelines without extensive engineering support
- Implement robust data quality testing frameworks that ensure data integrity throughout the entire data lifecycle
- Establish data engineering best practices, including version control, CI/CD for data pipelines, and automated testing
- Collaborate with ML/AI teams to build scalable feature engineering pipelines that support both batch and real-time data processing
- Develop reusable patterns for common data integration scenarios that can be leveraged across the organization
- Work closely with infrastructure teams to optimize our Kubernetes-based data platform for performance and reliability
- Mentor junior engineers and advocate for engineering excellence in data practices
Knowledge and Experience
- At least a Bachelor's degree in Computer Science, Computer Engineering, Data Science, Mathematics, Engineering, or related disciplines.
- 5+ years of professional experience in data engineering, with at least 2 years working on enterprise-scale data platforms
- Deep expertise with orchestrating workflows, performance optimization, and operational management
- Strong understanding of data transformation techniques, including experience with testing frameworks and deployment strategies
- Experience with stream processing frameworks and technologies
- Proficiency with SQL and Python for data transformation and pipeline development
- Familiarity with containerized application deployment
- Experience implementing data quality frameworks and automated testing for data pipelines
- Ability to work cross-functionally with data scientists, ML engineers, and business stakeholders
Preferred Qualifications
- Experience with self-hosted data orchestration platforms (rather than managed services)
- Background in implementing data contracts or schema governance
- Knowledge of ML/AI data pipeline requirements and feature engineering
- Experience with real-time data processing and streaming architectures
- Familiarity with data modeling and warehouse design principles
- Prior experience in a technical leadership role
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Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.