Senior Director of Data Platform Engineering
New
J
JobgetherData infrastructure
Based in the United States, U.S. East Coast and West Coast time zonesFull-TimeDirector
SalaryAnticipated base salary range of $261,000–$357,200 USD
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Job Details
- Experience
- 10+ years of relevant professional experience; at least 5 years of direct people management experience
- Required Skills
- People ManagementData engineering
Requirements
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
- 10+ years of relevant professional experience.
- At least 5 years of direct people management experience, including leadership of managers and multiple engineering teams.
- Experience leading a data engineering or data platform organization in a large-scale production environment.
- Experience developing and operating shared data platforms or infrastructure that enable engineering teams to build and manage their own data pipelines.
- Experience owning strategy and technical roadmaps for large-scale data infrastructure, database platforms, or distributed data systems.
- Experience leading data infrastructure modernization, architecture evolution, or technical-debt reduction initiatives.
- Knowledge of database engineering, data governance, data quality, and operational data architecture.
- Ability to work effectively across U.S. East Coast and West Coast time zones.
- Experience partnering with or leading an Analytics Engineering function is highly valued.
- Experience in regulated or data-intensive industries, particularly financial services or lending, is preferred.
Responsibilities
- Lead and evolve teams responsible for database engineering, data capture, data curation, production experience, and data governance.
- Define the long-term strategy, technical vision, and roadmap for data infrastructure.
- Modernize operational data architecture by simplifying systems, improving reliability and data quality, and reducing technical debt.
- Build scalable platforms, infrastructure, and tooling that enable engineering teams to develop, operate, and maintain data pipelines independently.
- Establish ownership models, engineering standards, operating practices, and technical processes.
- Develop engineering leaders and managers and support accountability, technical excellence, collaboration, and continuous improvement.
- Partner with Engineering, Analytics, Analytics Engineering, and Machine Learning Platform to identify shared needs and set priorities.
- Connect infrastructure investments to organizational priorities and communicate technical strategies to technical and non-technical stakeholders.
- Lead organizational and architectural changes as platform ownership, operating models, and infrastructure requirements evolve.
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