This role is designed for a mid-level data professional with 3–5 years of experience who bridges the gap between raw data and actionable intelligence. You shoul
Work type: remote
Location: Remote, US
Type: Full-time
This role is designed for a mid-level data professional with 3–5 years of experience who bridges the gap between raw data and actionable intelligence. You should have a strong command of ELT processes and analytics engineering, specifically within a SaaS environment. The ideal candidate isn’t necessarily a Machine Learning Engineer but understands how to structure data and engineer features to power downstream ML models and sophisticated business reporting. A major draw of this position is the flexibility of a 100% remote US-based work arrangement, backed by the stability of a FedRAMP-authorized cybersecurity firm. You’ll be working within a modern AWS stack (Redshift, Glue, Lambda) and have the opportunity to earn "above market" annual bonuses. It’s a high-impact role where you'll own the reliability and scalability of internal data pipelines. **You might be a good fit if you:** * Deeply understand SQL and how to design data models for cloud warehouses like Redshift or Snowflake. * Have professional experience using Python for data processing or pipeline orchestration. * Are interested in machine learning enablement (feature engineering) without wanting to manage model training yourself. * Meet the "U.S. Person" requirement necessary for FedRAMP compliance.
Description
Keeper Security is hiring a Data Engineer to join our growing Data Engineering organization, with a focus on building analytics platforms and enabling machine-learning-driven insights across the business. This is a 100% remote position, with an opportunity to work a hybrid schedule for candidates based in the El Dorado Hills, CA or Chicago, IL metro areas.
Keeper’s cybersecurity software is trusted by millions of people and thousands of organizations globally. Keeper is published in 23 languages and sold in over 150 countries. Join one of the fastest-growing cybersecurity companies and help design and build data pipelines and models that power analytics, operational reporting, and downstream machine learning use cases.
About Keeper
Keeper Security is transforming cybersecurity for organizations around the world with next-generation privileged access management. Keeper’s zero-trust and zero-knowledge cybersecurity solutions are FedRAMP and StateRAMP Authorized, FIPS 140-2 validated, as well as SOC 2 and ISO 27001 certified. Keeper deploys in minutes, not months, and seamlessly integrates with any tech stack to prevent breaches, reduce help desk costs and ensure compliance. Trusted by thousands of organizations to protect every user on every device, Keeper is the industry leader for best-in-class password management, secrets management, privileged access, secure remote access and encrypted messaging. Learn more at[ KeeperSecurity.com](https://www.keepersecurity.com/).
About the Role
As a Data Engineer, you will design and maintain analytics data pipelines and data models that support reporting, dashboards, and ML-adjacent workflows. You will work closely with data analysts, ML engineers, and business stakeholders to ensure data is reliable, well-modeled, and accessible. This role is ideal for a mid-level data engineer who is strong in analytics engineering and interested in supporting machine learning use cases without owning model development.
Responsibilities