Data Engineer, Analytics & Machine Learning Enablement

Keeper Security is seeking a Data Engineer focused on building analytics data pipelines and ML-ready workflows. This remote role offers flexibility, with an optional hybrid schedule for candidates in California or Illinois. The position emphasizes collaboration with analysts and ML engineers to enable reliable analytics and modeling capabilities across the organization.

Responsibilities

• Design and maintain ELT pipelines to ingest and transform data from core operational systems
• Create 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 promote 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 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

Technologies

• Python
• SQL
• Amazon Redshift
• Snowflake
• BigQuery
• S3
• Glue
• Lambda
• Step Functions
• dbt

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 Candidate Privacy Notice

Keeper collects and uses data throughout the recruitment process to assess your qualifications and manage interviews. Data may be provided by you, generated during the process, or obtained from others.

• Data We Collect: Contact details, CV/resume, cover letter; employment history, qualifications, work eligibility; application responses and uploaded documents
• Data We Generate: Interview notes, assessments, communications; scheduling information
• Information From Others: Referrals, public professional profiles, background verification (post offer)
• Voluntary Diversity Information: Optional data on race/ethnicity, gender, disability status, veteran status to comply with EEOC requirements
• How We Use Your Data: Assess suitability; manage interviews; consider for other roles; comply with employment laws
• Legal Basis: Legitimate interests; contractual steps; legal/regulatory compliance
• Sharing: Internal teams and third-party service providers; diversity data is not shared with hiring managers
• Third Party Safeguards: Contracts to protect data with appropriate safeguards
• International Transfers: Data may be accessed globally with safeguards in place
• Security: Technical and organizational measures to protect data
• Retention: Data kept for 24 months from last activity, with exceptions for consent or hire
• Your Rights: Access, correction, deletion, objection, data portability, complaint
• Automated Decisions: No hiring decisions are made solely by automated processing
• Contact: [email protected]