Senior Data Engineer

Description

About Cyera

Come join the company building the security operating model for the age of AI. AI has changed how data is used - and security must change with it. Cyera's mission is to empower businesses to accelerate AI Adoption by defining a holistic approach to securing AI - from data to access to model. Instead of perimeter controls and static policies, Cyera provides a unified control plane that understands relationships between data, access, and behaviors across humans, systems, and AI. Backed by the world’s leading investors and working with a large and growing list of Fortune 1000 companies, we are looking for world-class talent to join us as we usher in the new era of data and AI security.

About the Role

We’re looking for a Senior Data Engineer to join our Research Engineering Team and play a pivotal role in shaping the data infrastructure that powers Cyera’s innovative solutions. In this role, you’ll design, build, and scale data pipelines and data warehouses from the ground up, creating the backbone for the world’s leading data classification engine. You’ll collaborate closely with researchers and machine learning experts to enable the development of advanced models, ensuring a seamless flow of high-quality, reliable, and well-structured data. Your contributions will directly impact the scalability, performance, and precision of our platform, advancing our mission to protect critical data.

What You’ll Do

• Design and build scalable batch and streaming data pipelines that process complex datasets from diverse sources, enabling reliable and high-performance model training and inference.
• Collaborate closely with researchers and data scientists to deliver high-quality, structured datasets that accelerate experimentation and model iteration.
• Lead large-scale historical backfills and migration initiatives to ensure data consistency and integrity across evolving storage and compute platforms.
• Optimize data workflows through advanced query tuning, indexing, partitioning, and cost optimization strategies to support efficient large-scale analytics.
• Architect and maintain high-performance cloud-based data platforms using modern data stack components across AWS, GCP, or Azure.
• Operate distributed data processing engines to handle massive volumes of structured and unstructured data.
• Design and implement event-driven architectures using large-scale queue systems such as Kafka or SQS to ensure reliable and efficient data movement.
• Develop automated monitoring and validation systems that guarantee uptime, schema compatibility, and pipeline reliability.
• Deploy and manage data infrastructure in containerized, Kubernetes-based environments to support scalable and resilient services.

Why Join Us?

At Cyera, we own what we build and how we work. Cyerans are empowered to take initiative, move quickly, and turn ideas into impact.

We push boundaries by challenging the status quo, learning fast, and continuously raising the bar - for ourselves and for the industry.

We elevate together by lifting each other up, celebrating wins as a team, and recognizing that our success is shared.

Feel free to apply even if your experience doesn’t tick every box.

We’re building something special here - and we welcome Cyerans with diverse backgrounds, perspectives, and experiences.

Requirements

Who You Are

• 5+ years of experience in software engineering, with 2+ years focused on data engineering, building and operating large-scale data platforms.
• Proven experience designing and optimizing data pipelines, data warehouses, and big data solutions.
• Strong proficiency in data and advanced SQL, including: Complex analytical queries, Query performance tuning, Indexing & partitioning strategies
• Experience working with Relational and NoSQL databases
• Large-scale queue systems (Kafka, SQS, etc.)
• Experience working with Distributed processing engines
• Strong background in distributed systems and event-driven architectures.
• Experience working with cloud-native infrastructure and high-scale systems.
• Practical experience deploying and operating services in Kubernetes-based environments.
• Ability to thrive in a fast-paced research environment, solving complex data challenges with scalable and innovative solutions.

Nice-to-Haves

• Experience with additional data processing frameworks beyond the core stack.
• Background in cybersecurity-related data infrastructure projects.
• Familiarity with advanced machine learning workflows and their unique data challenges.
• Contributions to open-source data engineering tools or frameworks.
• Data lakes and modern storage formats (Delta Lake, Iceberg, Snowflake)