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Job Description

Okta is hiring a Principal Data Engineer, People Data (hybrid) to architect and deliver scalable data platforms that power candidate and employee lifecycle insights.

Responsibilities

  • Design, build, and continuously evolve high-scale data solutions to act as reference architecture and reduce friction for enterprise data access
  • Create data quality frameworks including monitoring, anomaly detection, and alerting, with governance, lineage tracking, and change management rigor for externally reported metrics
  • Drive consistent data modeling patterns, naming conventions, documentation standards, and metric governance across the data organization
  • Lead cross-functional technical initiatives across data verticals to accelerate delivery and harden data systems
  • Make sound technical decisions in ambiguous environments, balancing short-term execution with long-term infrastructure investment
  • Champion Data Contracts by implementing data contracts and schema evolution practices to support reliable outcomes across global product teams
  • Mentor and scale: mentor senior engineers, lead cross-functional task forces, and build a culture of engineering excellence and data-driven decision making
  • Stay current on data landscape developments, adopting and advocating emerging technologies and practices to shape the team’s long-term direction

Requirements

  • 10+ years in data engineering with proven senior or lead experience
  • Federal government compliance and security requirements experience is highly desirable
  • Expert-level skills in SQL, ETL/ELT using Airflow and dbt, and MPP databases such as Snowflake and Redshift
  • Extensive hands-on experience with AWS services including S3, Lambda, EMR, ECR, and EKS
  • People Data expertise focused on HR data: candidate lifecycle, employee records, compensation, and organizational data
  • Experience designing data models for recruiting analytics, engagement signals, and workforce planning metrics
  • Familiarity with Workday data structures is a bonus
  • Experience building and maintaining batch and real-time pipelines using Spark and Kafka
  • Deep experience with modern lakehouse and warehouse architectures (including Databricks and Snowflake) and modern file formats such as Iceberg and Delta
  • Proven ability to integrate AI tools to optimize or redesign workflows with measurable impact (efficiency gains, quality improvements)
  • Track record of hands-on collaboration with Data Science, Business, and Product teams

Technologies

  • SQL
  • Airflow
  • dbt
  • Snowflake
  • Redshift
  • AWS (S3, Lambda, EMR, ECR, EKS)
  • Spark
  • Kafka
  • Databricks
  • Iceberg
  • Delta

Okta Experience

  • Supporting Your Well-Being
  • Driving Social Impact
  • Developing Talent and Fostering Connection + Community

Location: Washington, DC (hybrid) | Compensation: USD 197,000 - 270,600 per yearly | Minimum experience: 10 years

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