Grip Security is looking for a Senior Data Platform Engineer to join our community!

We are a fast-growing startup in the software-as-a-service and AI Security Industry. We provide innovative solutions to securing the whole organization-to-SaaS surface. (More details: https://grip.security)

Using the newest technologies, we're working on solving a huge problem all enterprises face today - to govern the accessibility of all their employees to all 3rd party vendors (GitHub, SendGrid, Atlassian, and thousands more!), and ensure there is no leftover/unwanted access to any of the organization's SaaS and AI assets. The SaaS and AI security field is complex and challenging; therefore, we're looking for super-talented people, who are not afraid of technical challenges and breaking down barriers to achieve good solutions.

The job

As a Senior Data Platform Engineer, you will play a key role in building and evolving Grip’s modern data platform - the infrastructure that powers product features and analytics across the company.

You will focus on designing and operating scalable, reliable data systems and platform tooling that support our Data Lakehouse, enabling engineers, analysts and research teams to work with data efficiently and with minimal friction.

Responsibilities

• Design, build and operate a cloud-native modern data platform.
• Develop and optimize data processing frameworks and pipelines across batch and streaming workloads.
• Improve developer experience and platform usability through tooling and automation.
• Lead and support large-scale data migrations and architectural improvements.
• Drive best practices around infrastructure, CI/CD, testing, and system design.
• Collaborate with developers, analysts, data scientists and other stakeholders to develop new products and features.
• Contribute to a strong engineering culture of ownership, learning, and knowledge sharing.

Requirements

• 5+ years of hands-on experience building scalable data infrastructure, particularly around data lake or data warehouse architectures.
• Proven experience designing, building and operating production-grade systems and services.
• Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and hands-on experience with modern data platforms and tools (e.g., Spark, Kafka, Airflow, dbt, open table formats, or similar).
• Strong programming skills in Python and SQL.
• Independent, proactive, and ownership-driven mindset.
• Background in data platform engineering, backend engineering, DevOps, or DBA - strong advantage.
• Experience with containerization technologies - advantage.