Principal Data Engineer, People Data
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