[Hiring] Data Engineer, Analytics & Machine Learning Enablement @Keeper Security

Role 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.

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

• Build and maintain ELT pipelines that ingest and transform data from operational systems
• Develop analytics-ready data models to support reporting, KPIs, and downstream ML use cases
• Collaborate with analysts and ML engineers to ensure data structures meet modeling and feature needs
• Implement data quality checks, validation, and testing to ensure accuracy and reliability
• Optimize data pipeline performance, scalability, and cost efficiency
• Support data preparation and feature engineering workflows for machine learning initiatives
• Document data models, transformations, and lineage to support reuse and data literacy
• Partner with security and platform teams to ensure data governance and privacy requirements are met

Qualifications

• 3–5 years of experience in data engineering or backend data systems (SaaS experience preferred)
• Strong proficiency in SQL and experience designing analytics data models
• Working knowledge of Python for data processing or pipeline orchestration
• Experience working with cloud data warehouses such as Amazon Redshift (Snowflake or BigQuery acceptable)
• Familiarity with AWS data services such as S3, Glue, Lambda, or Step Functions
• Understanding of ELT best practices, data modeling, and schema design
• Exposure to supporting machine learning workflows through data preparation or feature engineering
• Knowledge of data security and privacy principles, including handling regulated data (PII, PHI)
• Strong software engineering fundamentals, including version control, testing, and CI/CD practices
• Bachelor’s degree in Computer Science, Engineering, Statistics, or a related field
• Due to FedRAMP requirements, candidates must be a U.S. Person

Preferred Qualifications

• Experience with DBT or analytics engineering frameworks
• Familiarity with feature stores or ML pipelines
• Experience supporting analytics or ML use cases for multiple business teams
• Interest in applied machine learning and data-driven products

Benefits

• Medical, Dental & Vision (Inclusive of domestic partnerships)
• Employer Paid Life Insurance & Employee/Spouse/Child Supplemental life
• Voluntary Short/Long Term Disability Insurance
• 401k (Roth/Traditional)
• A generous PTO plan that celebrates your commitment and seniority (including paid Bereavement/Jury Duty, etc)
• Above market annual bonuses