Senior Data Engineer, Data Infrastructure
Shift4 - Herzliya, Tel Aviv District, Israel
Posted Apr 20, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
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- 401(k) match
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Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Senior Data Engineer, Data Infrastructure Herzliya, Tel Aviv District, Israel Overview Shift4 (NYSE: FOUR) is boldly redefining commerce by simplifying complex payments ecosystems across the world. As the leader in commerce-enabling technology, Shift4 powers billions of transactions annually for hundreds of thousands of businesses in virtually every industry. For more information, visit www.shift4.com . Shift4 is looking for a Senior Data Engineer to join our Data Platform team. We are seeking a hands-on individual with experience in building and scaling modern data infrastructure, passionate about exploring AI technologies and applying them to enhance and evolve our data systems. This role is ideal for someone focused on data systems, performance, automation, and reliability, who will design, build, and maintain core components of our data pipelines, storage, monitoring, and observability stack, with a strong focus on improving workflows and system capabilities, while embracing the Shift4 way. Responsibilities: - Build and maintain scalable, reliable, and high-performance data infrastructure across cloud and on-prem environments - Partner with engineering, analytics, and observability teams to support data flow from ingestion to consumption - Develop infrastructure as code and automation tools to improve deployment, monitoring, and recovery - Help troubleshoot performance bottlenecks and reliability issues in large-scale data pipelines - Implement data quality processes aligned with security standards to ensure accuracy, consistency, and compliance with financial regulations and PCI requirements. - Continuously improve the performance and efficiency of the data platform with proactive tuning and benchmarking - Proactively explore and apply AI tools to enhance efficiency across
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