Senior Data Engineer

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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.

We emphasize building systems that are maintainable, scalable, and focused on enabling self‑service data access while maintaining high standards for data quality and governance. The ideal candidate is a problem‑solver who enjoys working on complex data systems and is passionate about data quality. You thrive in collaborative environments but can also work independently to deliver solutions, communicating complex technical concepts clearly to both technical and non‑technical stakeholders.

• Design, build, and maintain our on‑premises data orchestration platform using 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.

• 5+ years of professional experience in data engineering, with at least 2 years working on enterprise‑scale data platforms.
• Demonstrated experience 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 containerised 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.

• 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 leveraging AI tools (e.g., Git Hub Copilot, Cursor, Claude Code) to debug, develop unit tests and generate test cases from requirements documents.
• Experience with real‑time data processing and streaming architectures.
• Familiarity with data modelling and warehouse design principles.
• Prior experience in a technical leadership role.

• Not Applicable

• Full-time

• Information Technology

Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics.