The Role
Design, build, and optimize high-performance backend services and large-scale data pipelines on Databricks. Improve throughput, reliability, and observability of distributed data workflows, collaborate with cross-functional teams, and own end-to-end data platform architecture and production troubleshooting.
Summary Generated by Built In
We are seeking a highly skilled Senior Software Engineer to join our team responsible for large‑scale data processing, distributed computation, and performance‑critical backend services. This role is ideal for an experienced backend engineer with a strong Python background who has built and optimized data pipelines at scale.
You will design, build, and optimize systems that process large volumes of data using technologies such as Python, Databricks, and modern cloud‑native tooling. This is a senior technical position where architectural thinking, hands‑on coding ability, and ownership of end‑to‑end data workflows are essential.
Responsibilities
- Design, develop, and maintain scalable, high‑performance backend services in Python.
- Build and optimize large‑scale data processing pipelines running on Databricks.
- Implement efficient algorithms and data transformations to support analytical and operational needs.
- Optimize performance, throughput, and reliability of distributed data workflows.
- Collaborate closely with Data Scientists, Product Managers, and other engineering teams to translate requirements into scalable solutions.
- Implement monitoring, alerting, and observability for data workloads.
- Ensure code quality through best practices such as code reviews, testing, CI/CD, and documentation.
- Contribute to architectural decisions and technical strategy for the data platform.
- Troubleshoot production issues, perform root‑cause analysis, and optimize system stability.
Qualifications
- 5+ years of backend software engineering experience, with a strong focus on Python.
- Hands-on experience with Apache Spark, Databricks, or similar distributed-processing frameworks.
- Proven ability to design and optimize high-scale data pipelines handling large datasets.
- Strong understanding of distributed systems, parallel processing, and performance tuning.
- Familiarity with cloud environments (Azure, AWS, or GCP).
- Experience with modern CI/CD processes, testing frameworks, and code-quality standards.
- Strong understanding of data structures, algorithms, and system design.
- Excellent problem-solving skills and ability to work independently.
Nice-to-Have Skills
- Experience in data lakehouse architectures or cloud‑native data platforms.
- Familiarity with container technologies (Docker, Kubernetes).
- Background in cybersecurity, analytics platforms, or large-scale SaaS systems.
- Hands-on experience with AI concepts, LLMs, and agents.
Personal Qualities
- Ownership mindset and ability to drive initiatives end-to-end.
- Strong communication skills, both written and verbal.
- Ability to collaborate across teams in a fast-paced environment.
- Curiosity, adaptability, and passion for high-quality engineering.
What We Offer
- Opportunity to work on complex, large-scale data processing challenges.
- Strong engineering culture focused on excellence, transparency, and growth.
- Impactful role with broad technical ownership.
- Competitive compensation and benefits package.
About us
Cye helps security and risk leaders gain a clear, defensible view of their cyber exposure, grounded in financial impact and real-world attack paths. By continuously quantifying exposure and validating it in context, organizations can establish a strong baseline, prioritize decisions with confidence, and track measurable reduction over time.
Top Skills
Python,Databricks,Apache Spark,Azure,Aws,Gcp,Ci/Cd,Testing Frameworks
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
CYE’s optimized cyber risk quantification platform and expert guidance transform the way organizations manage cybersecurity.
Using AI, machine learning, and innovative technology, CYE visualizes attack routes, quantifies, mitigates, and communicates cyber risk, and matures organizational cybersecurity posture. In doing so, CYE provides clear and relevant insights that empower companies to make effective cybersecurity decisions. The company serves organizations in multiple industries globally.
Founded in 2012, with headquarters in Israel and operations around the world, CYE is funded by EQT Private Equity and 83North.
