• Own the EDA platform end-to-end • Optimize for scale • Build for researchers • Enable cross-functional users • Manage infrastructure • Provide support

• As a Senior Data Engineer, you will be the ideal person to support the Engineering area; your primary responsibility will be the scalable maintenance and creation of solutions for the data infrastructure. • Inspect, clean, transform, and model information, which is fundamental for decision-making. • Support the design of data processing components on Layer7 infrastructure that meet the specific needs of the company and its clients and suppliers. • Design, implement, and maintain data pipelines to integrate different sources. • Actively collaborate with data analysts, engineers, and cross-functional teams to understand and translate data requirements and propose tailored solutions. • Build metrics and implement observability tools to track and measure data pipeline performance for early incident detection. • Support the data governance process, maintaining data privacy criteria and the security regulations established by Layer7. • Document architectures, data flows, and process automation.

• You'll work across the full lifecycle of data engineering - from designing elegant solutions to deploying them in production • Building and maintaining data pipelines of varying complexity - from straightforward transformations to advanced probabilistic algorithms that drive our data science capabilities • Designing thoughtful solutions for new challenges, with emphasis on clean architecture and maintainability • Writing automated tests because we believe quality is built in, not bolted on • Fixing bugs and improving existing systems - our codebase evolves constantly • Exploring data when problems require investigation and analysis • Contributing to backend services and internal tools that support our data infrastructure • Deploying your work - you own it from concept to production

• Architect, scale, and maintain the backbone of our data ecosystem. • Transform massive volumes of raw signals into actionable intelligence. • Bridge the gap between high-level data strategy and hands-on technical excellence. • Lead the design, implementation, and optimization of distributed data architectures to support massive Batch & Streaming pipelines. • Ensure scalability, security, and performance of the infrastructure, maintaining high system availability (99.9%+) for analytics platforms. • Optimize storage solutions to balance high-speed processing with cost-efficiency. • Collaborate with software engineers and data scientists to seamlessly integrate AI-driven models into production data workflows. • Lead and mentor a team of 2 data engineers, fostering a culture of continuous improvement and technical excellence. • Set high standards for code quality, documentation, and rigorous peer reviews. • Oversee project execution, delegate responsibilities, and act as the technical point of escalation for complex data-related roadblocks. • Implement robust monitoring, alerting, and automated testing (Data Quality) to ensure the integrity of the data team's output. • Ensure data security and GDPR compliance across all international jurisdictions and workflows. • Identify opportunities to leverage new technologies or improve existing workflows to optimize data processing.