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Keeper Security, Inc.

Data Engineer, Analytics & Machine Learning Enablement

Posted Yesterday
Easy Apply
Remote or Hybrid
Hiring Remotely in US
Mid level
Easy Apply
Remote or Hybrid
Hiring Remotely in US
Mid level
Design, build, and maintain ELT pipelines and analytics-ready data models to support reporting, KPIs, and downstream ML use cases; implement data quality, optimize pipeline performance, document lineage, and ensure governance and privacy.
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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.

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

  • 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

Requirements

  • 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

Keeper Security, Inc. is an equal opportunity employer and participant in the U.S. Federal 

E-Verify program. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Classification: Exempt


Keeper Candidate Privacy Notice

This notice explains how Keeper Security processes your personal data during recruitment. Depending on the role and location, the Controller of personal data (the organization responsible for determining why and how personal data is processed) will be Keeper Security Inc. (US), Keeper Security EMEA Ltd. (Ireland), or Keeper Security APAC K.K (Japan).

1. Data We Collect

Information You provide:

  • Contact details, CV/resume, cover letter
  • Employment history, qualifications, work eligibility
  • Application responses and uploaded documents

Information We generate:

  • Interview notes, assessments, communications
  • Scheduling information

Information From Others:

  • Recruiter/referral information who submit your profile
  • References (with your consent, before final offer)
  • Public professional profiles
  • Background verification (post offer)

Voluntary Diversity and Equal Opportunity Information

  • We may ask you to voluntarily provide diversity information including race/ethnicity, gender, disability status and veteran status (US). Providing this information is optional and Keeper collects this data in order to comply with EEOC and similar requirements

2. How We Use Your Data

  • Assess your application and suitability
  • Manage interviews and recruitment workflow
  • Consider you for other/future roles (we may seek your consent to keep your information on our systems beyond the retention period specified)
  • Comply with employment law obligations

3. Legal Basis

  • Legitimate Interests (recruitment management, security and integrity of the hiring process)
  • Contracting steps (for progressed candidates)
  • Legal and regulatory compliance obligations; explicit consent where required

4. Who We Share Information With

Internal:

  • HR, hiring managers, interviewers*, IT support for system administration

*Note - diversity and equal opportunity data is not shared with hiring managers.

Third Parties:

Service providers who assist with:

  • Applicant tracking, recruitment systems and assessment providers
  • Background verification vendors (post offer)
  • Recruitment agencies (where applicable)
  • Tools to support communication, collaboration and to securely store your data

Keeper ensures that all our third parties are contractually bound to protect your personal data with adequate safeguards in place.

5. International Transfers

Your data may be accessed by Keeper entities globally as needed for the purposes of hiring and decision making. We protect any such data transfer between Keeper entities using appropriate safeguards under applicable data protection laws.

6. Security

We implement appropriate technical and organizational measures to protect your data, consistent with our industry leading security standards.

7. Retention

We keep your data for 24 months from your last application activity, then delete or anonymize it.

Exceptions:

  • You opt into our talent database for further retention by providing consent (extended retention)
  • You're hired (transfers to employee records)

8. Your Rights

You have the following rights and can contact us at the email below to exercise them:

  • Access, correct, or delete your data, subject to applicable law and retention requirements
  • Object to or restrict processing
  • Withdraw consent (where applicable)
  • Request data portability
  • Lodge a complaint with your data protection authority

If you become an employee, your rights regarding your employee record are governed by our internal Employee Privacy Notice and certain data will be retained as required under relevant laws such as employment or tax law. 

When you request access to your personal data, some information may be redacted if it includes the personal data of other individuals or information that we must protect in order to preserve their privacy rights.

9. Automated Decisions

Keeper does not make hiring decisions using solely automated processing.

10. Contact - Candidates can send privacy questions to: [email protected]


Top Skills

Sql,Python,Amazon Redshift,Snowflake,Bigquery,Aws S3,Aws Glue,Aws Lambda,Aws Step Functions,Elt,Dbt,Feature Stores,Ci/Cd,Version Control,Data Warehouses,Data Modeling,Schema Design

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